Drawing Lines in 2 Dimensions

Size: px
Start display at page:

Download "Drawing Lines in 2 Dimensions"

Transcription

1 Drawing Line in 2 Dimenion Drawing a traight line (or an arc) between two end point when one i limited to dicrete pixel require a bit of thought. Conider the following line uperimpoed on a 2 dimenional 7x7 pixel grid The pixel are indexed with the uual creen convention of x running from left to right and y running from top to bottom. Which pixel hould be et in order to repreent the line? If we increment our way vertically downward through the y value, etting the pixel in the appropriate x column a we go, we get The pixellated line ha gap in it. If, on the other hand, we increment our way horizontally acro through the x value, etting the pixel in the appropriate y can-line a we go, we get Thi i clearly a much more atifactory olution. We note, however, that had the line been longer in y than in x then the firt olution would have delivered the better reult. The magnitude of the lope of the line i the ey here. If the x range exceed the y range then the magnitude of the lope i le than 1 and we hould increment our way through x (and vice vera)

2 In fact, there are 4 cae to conider when electing which pixel hould be ued to contruct a continuou line 1. Poitive lope le than 1 2. Poitive lope greater than or equal to 1 3. Negative lope le than or equal to Negative lope greater than -1 If we now the end point of the line to be drawn we can alway calculate the lope y e y m = x e x A poitive lope (in creen co-ordinate) mean that the line i monotonic increaing (a x increae o doe y) whilt a negative lope indicate the oppoite (a x increae y decreae). The intercept, where the line meet (or would meet if long enough) the y axi i alo readily obtained c= y m x Of coure, thi relationhip hold for all pair of x and y value on the line o we can determine a y value for any x value and vice vera or, y = c + m x x = = y c y c m m m Now, if we conider only change in x and y we don t need to worry about the intercept except when determining the firt pixel to be plotted and, y = m x x = y m We hall conider two algorithm for drawing a 2D line on a diplay creen baed on the above principle; the Digital Differential Analyer and Breenham algorithm

3 The Digital Differential Analyer (DDA) Algorithm The DDA i a can-converion algorithm which ample a line at unit interval along one axi and determine integer value nearet the line for the other axi. Conider the line we have been looing at. The DDA will ample along the x axi in thi cae determining y value a it goe y y m + 1 = + If our line had a lope whoe magnitude wa greater than 1 (45º) then the DDA would need to ample along the y axi determining x value uing x = + 1 x + 1 m Thee equation will wor whether the lope i poitive or negative. When the lope i negative the x and y value will vary inverely but m will have the oppoite ign o all will be well Note that m i not necearily an integer, o the DDA require floating point arithmetic and rounding of the reult. Thi will low up the drawing proce even if implemented in hardware

4 Breenham Algorithm Breenham algorithm can-convert line more efficiently than the DDA by uing only integer arithmetic. It can alo be adapted to diplay curve. Conider, once again, a line with poitive lope le than 1 o we ample along x determining which y to plot. If we have jut plotted the pixel (x, y ) we now need to decide whether to plot (x +1, y ) or (x +1, y +1 ) a the next pixel on the line. Note that x +1 = x +1 and y +1 = y +1. Let the vertical diparitie of the pixel poition from the actual mathematical line be given by d 1 and d 2. Then, and, ( ) d y y m x c y 1 = = ( ) ( ) d2 = y + 1 y = y + 1 m x + 1 c Conider now the difference between thee two value ( ) d1 d2 = 2m x + 1 2y + 2c 1 If we let the difference between the x and y co-ordinate of the end point of the line be given by and, x = x x e y = y y e and if we init that thee endpoint co-ordinate are integer (which they will be if they are pecified a pixel) then we can write the lope of the line a a ratio of two integer m y = x If we now ubtitute thi ratio for m above we get and o, y d1 d 2 = 2 ( x + 1) 2 y + 2c 1 x - 4 -

5 where the term in quare bracet i contant and independent of the pixel poition. We hall call thi term b from now on. If we now define a deciion parameter a follow Then when p i poitive we hould chooe (x +1, y +1) a the pixel to plot and when it i negative we hould chooe (x +1, y ). Everything apart from the contant, b, in thi deciion can be calculated uing integer arithmetic o if we cam eliminate the need for b we have a method for plotting line uing integer arithmetic only. Conider the difference ( ) ( ) x d1 d2 = 2 y x 2 x y + 2 y + x 2c 1 ( ) p = x d d 1 2 = 2 y x 2 x y + b We have already noted that x +1 = x +1 o we can re-write thi a and where (y +1 -y ) i either 0 or 1 depending on the ign of p. So we have a recurrence equation which involve only integer calculation and all that i left i to determine a tarting value p 0 for it. Uing the tarting point of the line (x, y ) we can determine the intercept ( ) ( ) p p = 2 y x x 2 x y y ( ) p = p + 2 y 2 x y y y c = y mx = y x x and ubtituting thi into the equation for p we obtain p0 = 2 y x ============== - 5 -

6 Aliaing and Anti-aliaing When we produce line with Breenham algorithm, whilt we might be quite impreed with the peed at which we can generate them, we will not be overly enamoured with the way they loo. In general they will appear jagged, tepped, rateried. Thi effect i nown a aliaing, a term derived from ampling ignal at dicrete point in time and thu loing any information conveyed between thoe dicrete time. Our mathematically ideal line decribe a function whoe range i continuou but which our pixellated rater creen require to become dicrete. In effect we are ampling at dicrete point along the line and plotting the mot appropriate pixel for each ample. We have no choice of coure; the creen reolution contrain our ampling rate o aliaing i inevitable. Furthermore, our ideal mathematical line ha zero thicne but the line we wih to diplay mut have a thicne to be een. Indeed, we mae a virtue of thi requirement and put line of varying thicne to good ue. In computer graphic a traight line i, in reality, a thin rectangle and we mut treat it a uch. Conider the following line uperimpoed on a 2 dimenional 7x7 pixel grid Thi line ha a very clear thicne and i quite obviouly a filled rectangle. If we pixellate it, a we did with our mathematically ideal line previouly, we get The pixellated line diplay clear evidence of aliaing. Can we mae it more aethetically appealing? Of coure, the anwer i ye. We can anti-alia it. Anti-aliaing algorithm wor by partially illuminating pixel which are adjacent to thoe plotted by the line drawing algorithm (e.g. the DDA or Breenham algorithm). Thi mean that anti-aliaed line will be wider than wa probably intended. The two mot common method for anti-aliaing are filtering and uperampling

7 Filtering Thi technique i baed on the concept that each pixel ha an area of influence around it. If our rectangular-haped line overlap the area of influence of a pixel then that pixel hould be illuminated by an amount proportional to the degree of overlap. Thi amount i determined by a filter function. One popular filtering cheme i baed on circular area of influence which are one pixel in radiu. I.e. the area of influence of each pixel extend a far a the centre of it four nearet neighbour The filter function i defined to be a cone with it bae being the area of influence and it apex lying directly above the pixel centre, at a height which produce an overall volume for the cone of unity. The interection of a pixel area of influence with the rectangular line i then determined and the volume of the cone directly above that interection yield the amount of illumination to be applied to that pixel. Clearly the amount of illumination applied to any pixel will range from 0 (pixel area of influence totally outwith the line) up to 1 (pixel totally within the line). Thi i clearly a computationally expenive proce. In order to eep the computation time down it i normal to pre-calculate table of value for the filter function. The downide to thi i that the reulting algorithm are not very flexible the filter function, area of influence and palette ize are all fixed in a given table and any change to thee value will require a new table to be produced

8 Superampling Another technique for anti-aliaing ue the concept of ub-pixel. Each pixel i divided into, ay nine, ub-pixel We then count the number of ub-pixel that the line overlap. We need a reference point within each ub-pixel to ue in thi counting proce. It doen t matter where it i a long a we ue it conitently for all ub-pixel. A corner, uch a the top-left, i a popular choice. Centre would produce a more aethetically pleaing reult but at the cot of computational efficiency. The proportion of ub-pixel which the line overlap i then ued to determine the illumination, in dicrete tep from 0 through to 1. Clearly the larger the number of ub-pixel which the pixel i divided into, the finer the reolution that can be accomplihed in the illumination. Once again we have to trie a balance between aethetic and computation time. Thi will be determined by the need of the particular application

MAT 155: Describing, Exploring, and Comparing Data Page 1 of NotesCh2-3.doc

MAT 155: Describing, Exploring, and Comparing Data Page 1 of NotesCh2-3.doc MAT 155: Decribing, Exploring, and Comparing Data Page 1 of 8 001-oteCh-3.doc ote for Chapter Summarizing and Graphing Data Chapter 3 Decribing, Exploring, and Comparing Data Frequency Ditribution, Graphic

More information

Lecture 14: Minimum Spanning Tree I

Lecture 14: Minimum Spanning Tree I COMPSCI 0: Deign and Analyi of Algorithm October 4, 07 Lecture 4: Minimum Spanning Tree I Lecturer: Rong Ge Scribe: Fred Zhang Overview Thi lecture we finih our dicuion of the hortet path problem and introduce

More information

Quadrilaterals. Learning Objectives. Pre-Activity

Quadrilaterals. Learning Objectives. Pre-Activity Section 3.4 Pre-Activity Preparation Quadrilateral Intereting geometric hape and pattern are all around u when we tart looking for them. Examine a row of fencing or the tiling deign at the wimming pool.

More information

KS3 Maths Assessment Objectives

KS3 Maths Assessment Objectives KS3 Math Aement Objective Tranition Stage 9 Ratio & Proportion Probabilit y & Statitic Appreciate the infinite nature of the et of integer, real and rational number Can interpret fraction and percentage

More information

ES205 Analysis and Design of Engineering Systems: Lab 1: An Introductory Tutorial: Getting Started with SIMULINK

ES205 Analysis and Design of Engineering Systems: Lab 1: An Introductory Tutorial: Getting Started with SIMULINK ES05 Analyi and Deign of Engineering Sytem: Lab : An Introductory Tutorial: Getting Started with SIMULINK What i SIMULINK? SIMULINK i a oftware package for modeling, imulating, and analyzing dynamic ytem.

More information

Scan Conversion. CMP 477 Computer Graphics S. A. Arekete

Scan Conversion. CMP 477 Computer Graphics S. A. Arekete Scan Conversion CMP 477 Computer Graphics S. A. Areete What is Scan-Conversion? 2D or 3D objects in real world space are made up of graphic primitives such as points, lines, circles and filled polygons.

More information

An Intro to LP and the Simplex Algorithm. Primal Simplex

An Intro to LP and the Simplex Algorithm. Primal Simplex An Intro to LP and the Simplex Algorithm Primal Simplex Linear programming i contrained minimization of a linear objective over a olution pace defined by linear contraint: min cx Ax b l x u A i an m n

More information

A SIMPLE IMPERATIVE LANGUAGE THE STORE FUNCTION NON-TERMINATING COMMANDS

A SIMPLE IMPERATIVE LANGUAGE THE STORE FUNCTION NON-TERMINATING COMMANDS A SIMPLE IMPERATIVE LANGUAGE Eventually we will preent the emantic of a full-blown language, with declaration, type and looping. However, there are many complication, o we will build up lowly. Our firt

More information

Universität Augsburg. Institut für Informatik. Approximating Optimal Visual Sensor Placement. E. Hörster, R. Lienhart.

Universität Augsburg. Institut für Informatik. Approximating Optimal Visual Sensor Placement. E. Hörster, R. Lienhart. Univerität Augburg à ÊÇÅÍÆ ËÀǼ Approximating Optimal Viual Senor Placement E. Hörter, R. Lienhart Report 2006-01 Januar 2006 Intitut für Informatik D-86135 Augburg Copyright c E. Hörter, R. Lienhart Intitut

More information

CSE 250B Assignment 4 Report

CSE 250B Assignment 4 Report CSE 250B Aignment 4 Report March 24, 2012 Yuncong Chen yuncong@c.ucd.edu Pengfei Chen pec008@ucd.edu Yang Liu yal060@c.ucd.edu Abtract In thi project, we implemented the recurive autoencoder (RAE) a decribed

More information

Course Updates. Reminders: 1) Assignment #13 due Monday. 2) Mirrors & Lenses. 3) Review for Final: Wednesday, May 5th

Course Updates. Reminders: 1) Assignment #13 due Monday. 2) Mirrors & Lenses. 3) Review for Final: Wednesday, May 5th Coure Update http://www.phy.hawaii.edu/~varner/phys272-spr0/phyic272.html Reminder: ) Aignment #3 due Monday 2) Mirror & Lene 3) Review for Final: Wedneday, May 5th h R- R θ θ -R h Spherical Mirror Infinite

More information

Topics. Lecture 37: Global Optimization. Issues. A Simple Example: Copy Propagation X := 3 B > 0 Y := 0 X := 4 Y := Z + W A := 2 * 3X

Topics. Lecture 37: Global Optimization. Issues. A Simple Example: Copy Propagation X := 3 B > 0 Y := 0 X := 4 Y := Z + W A := 2 * 3X Lecture 37: Global Optimization [Adapted from note by R. Bodik and G. Necula] Topic Global optimization refer to program optimization that encompa multiple baic block in a function. (I have ued the term

More information

Delaunay Triangulation: Incremental Construction

Delaunay Triangulation: Incremental Construction Chapter 6 Delaunay Triangulation: Incremental Contruction In the lat lecture, we have learned about the Lawon ip algorithm that compute a Delaunay triangulation of a given n-point et P R 2 with O(n 2 )

More information

Polygon Side Lengths NAME DATE TIME

Polygon Side Lengths NAME DATE TIME Home Link 5- Polygon Side Length Find any miing coordinate. Plot and label the point on the coordinate grid. Draw the polygon by connecting the point. y a. Rectangle ABCD A: (, ) B: (-, ) The length of

More information

Algorithmic Discrete Mathematics 4. Exercise Sheet

Algorithmic Discrete Mathematics 4. Exercise Sheet Algorithmic Dicrete Mathematic. Exercie Sheet Department of Mathematic SS 0 PD Dr. Ulf Lorenz 0. and. May 0 Dipl.-Math. David Meffert Verion of May, 0 Groupwork Exercie G (Shortet path I) (a) Calculate

More information

Motivation: Level Sets. Input Data Noisy. Easy Case Use Marching Cubes. Intensity Varies. Non-uniform Exposure. Roger Crawfis

Motivation: Level Sets. Input Data Noisy. Easy Case Use Marching Cubes. Intensity Varies. Non-uniform Exposure. Roger Crawfis Level Set Motivation: Roger Crawfi Slide collected from: Fan Ding, Charle Dyer, Donald Tanguay and Roger Crawfi 4/24/2003 R. Crawfi, Ohio State Univ. 109 Eay Cae Ue Marching Cube Input Data Noiy 4/24/2003

More information

Representations and Transformations. Objectives

Representations and Transformations. Objectives Repreentation and Tranformation Objective Derive homogeneou coordinate tranformation matrice Introduce tandard tranformation - Rotation - Tranlation - Scaling - Shear Scalar, Point, Vector Three baic element

More information

Performance of a Robust Filter-based Approach for Contour Detection in Wireless Sensor Networks

Performance of a Robust Filter-based Approach for Contour Detection in Wireless Sensor Networks Performance of a Robut Filter-baed Approach for Contour Detection in Wirele Senor Network Hadi Alati, William A. Armtrong, Jr., and Ai Naipuri Department of Electrical and Computer Engineering The Univerity

More information

DAROS: Distributed User-Server Assignment And Replication For Online Social Networking Applications

DAROS: Distributed User-Server Assignment And Replication For Online Social Networking Applications DAROS: Ditributed Uer-Server Aignment And Replication For Online Social Networking Application Thuan Duong-Ba School of EECS Oregon State Univerity Corvalli, OR 97330, USA Email: duongba@eec.oregontate.edu

More information

Routing Definition 4.1

Routing Definition 4.1 4 Routing So far, we have only looked at network without dealing with the iue of how to end information in them from one node to another The problem of ending information in a network i known a routing

More information

Areas of Regular Polygons. To find the area of a regular polygon. The Solve It involves the area of a polygon.

Areas of Regular Polygons. To find the area of a regular polygon. The Solve It involves the area of a polygon. 10- Area of Regular Polygon Common Core State Standard G-MG.A.1 Ue geometric hape, their meaure, and their propertie to decribe object. Alo G-CO.D.1 MP 1, MP, MP 4, MP 6, MP 7 Objective To find the area

More information

1 The secretary problem

1 The secretary problem Thi i new material: if you ee error, pleae email jtyu at tanford dot edu 1 The ecretary problem We will tart by analyzing the expected runtime of an algorithm, a you will be expected to do on your homework.

More information

else end while End References

else end while End References 621-630. [RM89] [SK76] Roenfeld, A. and Melter, R. A., Digital geometry, The Mathematical Intelligencer, vol. 11, No. 3, 1989, pp. 69-72. Sklanky, J. and Kibler, D. F., A theory of nonuniformly digitized

More information

AN ALGORITHM FOR RESTRICTED NORMAL FORM TO SOLVE DUAL TYPE NON-CANONICAL LINEAR FRACTIONAL PROGRAMMING PROBLEM

AN ALGORITHM FOR RESTRICTED NORMAL FORM TO SOLVE DUAL TYPE NON-CANONICAL LINEAR FRACTIONAL PROGRAMMING PROBLEM RAC Univerity Journal, Vol IV, No, 7, pp 87-9 AN ALGORITHM FOR RESTRICTED NORMAL FORM TO SOLVE DUAL TYPE NON-CANONICAL LINEAR FRACTIONAL PROGRAMMING PROLEM Mozzem Hoain Department of Mathematic Ghior Govt

More information

IMPLEMENTATION OF AREA, VOLUME AND LINE SOURCES

IMPLEMENTATION OF AREA, VOLUME AND LINE SOURCES December 01 ADMS 5 P503I1 IMPEMENTATION OF AREA, VOUME AND INE SOURCES The Met. Office (D J Thomon) and CERC 1. INTRODUCTION ADMS model line ource, and area and volume ource with conve polgon bae area.

More information

Stochastic Search and Graph Techniques for MCM Path Planning Christine D. Piatko, Christopher P. Diehl, Paul McNamee, Cheryl Resch and I-Jeng Wang

Stochastic Search and Graph Techniques for MCM Path Planning Christine D. Piatko, Christopher P. Diehl, Paul McNamee, Cheryl Resch and I-Jeng Wang Stochatic Search and Graph Technique for MCM Path Planning Chritine D. Piatko, Chritopher P. Diehl, Paul McNamee, Cheryl Rech and I-Jeng Wang The John Hopkin Univerity Applied Phyic Laboratory, Laurel,

More information

TAM 212 Worksheet 3. Solutions

TAM 212 Worksheet 3. Solutions Name: Group member: TAM 212 Workheet 3 Solution The workheet i concerned with the deign of the loop-the-loop for a roller coater ytem. Old loop deign: The firt generation of loop wa circular, a hown below.

More information

Multi-Target Tracking In Clutter

Multi-Target Tracking In Clutter Multi-Target Tracking In Clutter John N. Sander-Reed, Mary Jo Duncan, W.B. Boucher, W. Michael Dimmler, Shawn O Keefe ABSTRACT A high frame rate (0 Hz), multi-target, video tracker ha been developed and

More information

The norm Package. November 15, Title Analysis of multivariate normal datasets with missing values

The norm Package. November 15, Title Analysis of multivariate normal datasets with missing values The norm Package November 15, 2003 Verion 1.0-9 Date 2002/05/06 Title Analyi of multivariate normal dataet with miing value Author Ported to R by Alvaro A. Novo . Original by Joeph

More information

Laboratory Exercise 2

Laboratory Exercise 2 Laoratory Exercie Numer and Diplay Thi i an exercie in deigning cominational circuit that can perform inary-to-decimal numer converion and inary-coded-decimal (BCD) addition. Part I We wih to diplay on

More information

Advanced Encryption Standard and Modes of Operation

Advanced Encryption Standard and Modes of Operation Advanced Encryption Standard and Mode of Operation G. Bertoni L. Breveglieri Foundation of Cryptography - AES pp. 1 / 50 AES Advanced Encryption Standard (AES) i a ymmetric cryptographic algorithm AES

More information

xy-monotone path existence queries in a rectilinear environment

xy-monotone path existence queries in a rectilinear environment CCCG 2012, Charlottetown, P.E.I., Augut 8 10, 2012 xy-monotone path exitence querie in a rectilinear environment Gregory Bint Anil Mahehwari Michiel Smid Abtract Given a planar environment coniting of

More information

Log1 Contest Round 2 Theta Geometry. 4 points each 1 What is the area of an isosceles right triangle with legs of length 3?

Log1 Contest Round 2 Theta Geometry. 4 points each 1 What is the area of an isosceles right triangle with legs of length 3? 009 00 Log Contet Round Theta Geometry Name: 4 point each What i the area of an iocele right triangle with leg of length? What i perimeter of a regular heptagon with ide of length 8? Matt built a foot

More information

Planning of scooping position and approach path for loading operation by wheel loader

Planning of scooping position and approach path for loading operation by wheel loader 22 nd International Sympoium on Automation and Robotic in Contruction ISARC 25 - September 11-14, 25, Ferrara (Italy) 1 Planning of cooping poition and approach path for loading operation by wheel loader

More information

VLSI Design 9. Datapath Design

VLSI Design 9. Datapath Design VLSI Deign 9. Datapath Deign 9. Datapath Deign Lat module: Adder circuit Simple adder Fat addition Thi module omparator Shifter Multi-input Adder Multiplier omparator detector: A = 1 detector: A = 11 111

More information

Computer Graphics : Bresenham Line Drawing Algorithm, Circle Drawing & Polygon Filling

Computer Graphics : Bresenham Line Drawing Algorithm, Circle Drawing & Polygon Filling Computer Graphics : Bresenham Line Drawing Algorithm, Circle Drawing & Polygon Filling Downloaded from :www.comp.dit.ie/bmacnamee/materials/graphics/006- Contents In today s lecture we ll have a loo at:

More information

OpenGL Graphics System. 2D Graphics Primitives. Drawing 2D Graphics Primitives. 2D Graphics Primitives. Mathematical 2D Primitives.

OpenGL Graphics System. 2D Graphics Primitives. Drawing 2D Graphics Primitives. 2D Graphics Primitives. Mathematical 2D Primitives. D Graphics Primitives Eye sees Displays - CRT/LCD Frame buffer - Addressable pixel array (D) Graphics processor s main function is to map application model (D) by projection on to D primitives: points,

More information

See chapter 8 in the textbook. Dr Muhammad Al Salamah, Industrial Engineering, KFUPM

See chapter 8 in the textbook. Dr Muhammad Al Salamah, Industrial Engineering, KFUPM Goal programming Objective of the topic: Indentify indutrial baed ituation where two or more objective function are required. Write a multi objective function model dla a goal LP Ue weighting um and preemptive

More information

ALIASING AND ALPHA Introduction to Graphics, Lecture 3. Anthony Steed , Jan Kautz

ALIASING AND ALPHA Introduction to Graphics, Lecture 3. Anthony Steed , Jan Kautz ALIASING AND ALPHA 2011 Introduction to Graphic, Lecture 3 Anthony Steed 2000-2006, Jan Kautz 2007 2012 Overview Plotting Pixel Aliaing Anti-aliaing Alpha Value Image Compoition Rule Porter-Duff Super-Sampling

More information

Localized Minimum Spanning Tree Based Multicast Routing with Energy-Efficient Guaranteed Delivery in Ad Hoc and Sensor Networks

Localized Minimum Spanning Tree Based Multicast Routing with Energy-Efficient Guaranteed Delivery in Ad Hoc and Sensor Networks Localized Minimum Spanning Tree Baed Multicat Routing with Energy-Efficient Guaranteed Delivery in Ad Hoc and Senor Network Hanne Frey Univerity of Paderborn D-3398 Paderborn hanne.frey@uni-paderborn.de

More information

Karen L. Collins. Wesleyan University. Middletown, CT and. Mark Hovey MIT. Cambridge, MA Abstract

Karen L. Collins. Wesleyan University. Middletown, CT and. Mark Hovey MIT. Cambridge, MA Abstract Mot Graph are Edge-Cordial Karen L. Collin Dept. of Mathematic Weleyan Univerity Middletown, CT 6457 and Mark Hovey Dept. of Mathematic MIT Cambridge, MA 239 Abtract We extend the definition of edge-cordial

More information

SIMIT 7. Component Type Editor (CTE) User manual. Siemens Industrial

SIMIT 7. Component Type Editor (CTE) User manual. Siemens Industrial SIMIT 7 Component Type Editor (CTE) Uer manual Siemen Indutrial Edition January 2013 Siemen offer imulation oftware to plan, imulate and optimize plant and machine. The imulation- and optimizationreult

More information

Interface Tracking in Eulerian and MMALE Calculations

Interface Tracking in Eulerian and MMALE Calculations Interface Tracking in Eulerian and MMALE Calculation Gabi Luttwak Rafael P.O.Box 2250, Haifa 31021,Irael Interface Tracking in Eulerian and MMALE Calculation 3D Volume of Fluid (VOF) baed recontruction

More information

Diffraction I Version 1.0 : March 12, 2019

Diffraction I Version 1.0 : March 12, 2019 Diffraction I Interference an Diffraction of Light Through Slit: The Jut Give Me The Formulae Verion! Steve Smith March 12, 2019 Content 1 Introuction 3 1.1 Huygen Principle.............................................

More information

Maneuverable Relays to Improve Energy Efficiency in Sensor Networks

Maneuverable Relays to Improve Energy Efficiency in Sensor Networks Maneuverable Relay to Improve Energy Efficiency in Senor Network Stephan Eidenbenz, Luka Kroc, Jame P. Smith CCS-5, MS M997; Lo Alamo National Laboratory; Lo Alamo, NM 87545. Email: {eidenben, kroc, jpmith}@lanl.gov

More information

Motion Control (wheeled robots)

Motion Control (wheeled robots) 3 Motion Control (wheeled robot) Requirement for Motion Control Kinematic / dynamic model of the robot Model of the interaction between the wheel and the ground Definition of required motion -> peed control,

More information

SLA Adaptation for Service Overlay Networks

SLA Adaptation for Service Overlay Networks SLA Adaptation for Service Overlay Network Con Tran 1, Zbigniew Dziong 1, and Michal Pióro 2 1 Department of Electrical Engineering, École de Technologie Supérieure, Univerity of Quebec, Montréal, Canada

More information

CENTER-POINT MODEL OF DEFORMABLE SURFACE

CENTER-POINT MODEL OF DEFORMABLE SURFACE CENTER-POINT MODEL OF DEFORMABLE SURFACE Piotr M. Szczypinki Iintitute of Electronic, Technical Univerity of Lodz, Poland Abtract: Key word: Center-point model of deformable urface for egmentation of 3D

More information

Laboratory Exercise 6

Laboratory Exercise 6 Laboratory Exercie 6 Adder, Subtractor, and Multiplier The purpoe of thi exercie i to examine arithmetic circuit that add, ubtract, and multiply number. Each type of circuit will be implemented in two

More information

Analysis of slope stability

Analysis of slope stability Engineering manual No. 8 Updated: 02/2016 Analyi of lope tability Program: Slope tability File: Demo_manual_08.gt In thi engineering manual, we are going to how you how to verify the lope tability for

More information

Mid-term review ECE 161C Electrical and Computer Engineering University of California San Diego

Mid-term review ECE 161C Electrical and Computer Engineering University of California San Diego Mid-term review ECE 161C Electrical and Computer Engineering Univerity of California San Diego Nuno Vaconcelo Spring 2014 1. We have een in cla that one popular technique for edge detection i the Canny

More information

A Boyer-Moore Approach for. Two-Dimensional Matching. Jorma Tarhio. University of California. Berkeley, CA Abstract

A Boyer-Moore Approach for. Two-Dimensional Matching. Jorma Tarhio. University of California. Berkeley, CA Abstract A Boyer-Moore Approach for Two-Dimenional Matching Jorma Tarhio Computer Science Diviion Univerity of California Berkeley, CA 94720 Abtract An imple ublinear algorithm i preented for two-dimenional tring

More information

Generic Traverse. CS 362, Lecture 19. DFS and BFS. Today s Outline

Generic Traverse. CS 362, Lecture 19. DFS and BFS. Today s Outline Generic Travere CS 62, Lecture 9 Jared Saia Univerity of New Mexico Travere(){ put (nil,) in bag; while (the bag i not empty){ take ome edge (p,v) from the bag if (v i unmarked) mark v; parent(v) = p;

More information

Minimum congestion spanning trees in bipartite and random graphs

Minimum congestion spanning trees in bipartite and random graphs Minimum congetion panning tree in bipartite and random graph M.I. Otrovkii Department of Mathematic and Computer Science St. John Univerity 8000 Utopia Parkway Queen, NY 11439, USA e-mail: otrovm@tjohn.edu

More information

On successive packing approach to multidimensional (M-D) interleaving

On successive packing approach to multidimensional (M-D) interleaving On ucceive packing approach to multidimenional (M-D) interleaving Xi Min Zhang Yun Q. hi ankar Bau Abtract We propoe an interleaving cheme for multidimenional (M-D) interleaving. To achieved by uing a

More information

Variable Resolution Discretization in the Joint Space

Variable Resolution Discretization in the Joint Space Variable Reolution Dicretization in the Joint Space Chritopher K. Monon, David Wingate, and Kevin D. Seppi {c,wingated,keppi}@c.byu.edu Computer Science, Brigham Young Univerity Todd S. Peteron peterto@uvc.edu

More information

Hassan Ghaziri AUB, OSB Beirut, Lebanon Key words Competitive self-organizing maps, Meta-heuristics, Vehicle routing problem,

Hassan Ghaziri AUB, OSB Beirut, Lebanon Key words Competitive self-organizing maps, Meta-heuristics, Vehicle routing problem, COMPETITIVE PROBABIISTIC SEF-ORGANIZING MAPS FOR ROUTING PROBEMS Haan Ghaziri AUB, OSB Beirut, ebanon ghaziri@aub.edu.lb Abtract In thi paper, we have applied the concept of the elf-organizing map (SOM)

More information

UC Berkeley International Conference on GIScience Short Paper Proceedings

UC Berkeley International Conference on GIScience Short Paper Proceedings UC Berkeley International Conference on GIScience Short Paper Proceeding Title A novel method for probabilitic coverage etimation of enor network baed on 3D vector repreentation in complex urban environment

More information

Laboratory Exercise 6

Laboratory Exercise 6 Laboratory Exercie 6 Adder, Subtractor, and Multiplier The purpoe of thi exercie i to examine arithmetic circuit that add, ubtract, and multiply number. Each circuit will be decribed in Verilog and implemented

More information

Cutting Stock by Iterated Matching. Andreas Fritsch, Oliver Vornberger. University of Osnabruck. D Osnabruck.

Cutting Stock by Iterated Matching. Andreas Fritsch, Oliver Vornberger. University of Osnabruck. D Osnabruck. Cutting Stock by Iterated Matching Andrea Fritch, Oliver Vornberger Univerity of Onabruck Dept of Math/Computer Science D-4909 Onabruck andy@informatikuni-onabrueckde Abtract The combinatorial optimization

More information

How to Select Measurement Points in Access Point Localization

How to Select Measurement Points in Access Point Localization Proceeding of the International MultiConference of Engineer and Computer Scientit 205 Vol II, IMECS 205, March 8-20, 205, Hong Kong How to Select Meaurement Point in Acce Point Localization Xiaoling Yang,

More information

A METHOD OF REAL-TIME NURBS INTERPOLATION WITH CONFINED CHORD ERROR FOR CNC SYSTEMS

A METHOD OF REAL-TIME NURBS INTERPOLATION WITH CONFINED CHORD ERROR FOR CNC SYSTEMS Vietnam Journal of Science and Technology 55 (5) (017) 650-657 DOI: 10.1565/55-518/55/5/906 A METHOD OF REAL-TIME NURBS INTERPOLATION WITH CONFINED CHORD ERROR FOR CNC SYSTEMS Nguyen Huu Quang *, Banh

More information

Gray-level histogram. Intensity (grey-level) transformation, or mapping. Use of intensity transformations:

Gray-level histogram. Intensity (grey-level) transformation, or mapping. Use of intensity transformations: Faculty of Informatic Eötvö Loránd Univerity Budapet, Hungary Lecture : Intenity Tranformation Image enhancement by point proceing Spatial domain and frequency domain method Baic Algorithm for Digital

More information

Image authentication and tamper detection using fragile watermarking in spatial domain

Image authentication and tamper detection using fragile watermarking in spatial domain International Journal of Advanced Reearch in Computer Engineering & Technology (IJARCET) Volume 6, Iue 7, July 2017, ISSN: 2278 1323 Image authentication and tamper detection uing fragile watermarking

More information

Power Aware Location Aided Routing in Mobile Ad-hoc Networks

Power Aware Location Aided Routing in Mobile Ad-hoc Networks International Journal of Scientific and Reearch Publication, Volume, Iue 1, December 01 1 Power Aware Location Aided Routing in Mobile Ad-hoc Network Anamika Computer Science, Inderprataha Engineering

More information

Loop Forming Snake-like Robot ACM-R7 and Its Serpenoid Oval Control

Loop Forming Snake-like Robot ACM-R7 and Its Serpenoid Oval Control The 21 IEEE/RSJ International Conference on Intelligent Robot and Sytem October 18-22, 21, Taipei, Taiwan Loop Forming Snake-like Robot ACM-R7 and It Serpenoid Oval Control Taro Ohahi, Hiroya Yamada and

More information

Trainable Context Model for Multiscale Segmentation

Trainable Context Model for Multiscale Segmentation Trainable Context Model for Multicale Segmentation Hui Cheng and Charle A. Bouman School of Electrical and Computer Engineering Purdue Univerity Wet Lafayette, IN 47907-1285 {hui, bouman}@ ecn.purdue.edu

More information

3D MODELLING WITH LINEAR APPROACHES USING GEOMETRIC PRIMITIVES

3D MODELLING WITH LINEAR APPROACHES USING GEOMETRIC PRIMITIVES MAKARA, TEKNOLOGI, VOL. 9, NO., APRIL 5: 3-35 3D MODELLING WITH LINEAR APPROACHES USING GEOMETRIC PRIMITIVES Mochammad Zulianyah Informatic Engineering, Faculty of Engineering, ARS International Univerity,

More information

Z-transformation in simulation of continuous system

Z-transformation in simulation of continuous system Z-tranformation in imulation of continuou tem Mirolav Kašpar, Alexandr Štefek Univerit of defence Abtract Motl ued method for continuou tem imulation i uing algorithm for numeric olving of differential

More information

Towards an Efficient Optimal Trajectory Planner for Multiple Mobile Robots

Towards an Efficient Optimal Trajectory Planner for Multiple Mobile Robots Toward an Efficient Optimal Trajectory Planner for Multiple Mobile Robot Jaon Thoma, Alan Blair, Nick Barne Department of Computer Science and Software Engineering The Univerity of Melbourne, Victoria,

More information

Increasing Throughput and Reducing Delay in Wireless Sensor Networks Using Interference Alignment

Increasing Throughput and Reducing Delay in Wireless Sensor Networks Using Interference Alignment Int. J. Communication, Network and Sytem Science, 0, 5, 90-97 http://dx.doi.org/0.436/ijcn.0.50 Publihed Online February 0 (http://www.scirp.org/journal/ijcn) Increaing Throughput and Reducing Delay in

More information

Lecture Outline. Global flow analysis. Global Optimization. Global constant propagation. Liveness analysis. Local Optimization. Global Optimization

Lecture Outline. Global flow analysis. Global Optimization. Global constant propagation. Liveness analysis. Local Optimization. Global Optimization Lecture Outline Global flow analyi Global Optimization Global contant propagation Livene analyi Adapted from Lecture by Prof. Alex Aiken and George Necula (UCB) CS781(Praad) L27OP 1 CS781(Praad) L27OP

More information

Chapter 13 Non Sampling Errors

Chapter 13 Non Sampling Errors Chapter 13 Non Sampling Error It i a general aumption in the ampling theory that the true value of each unit in the population can be obtained and tabulated without any error. In practice, thi aumption

More information

Part 1 A New Number Format: The Unum

Part 1 A New Number Format: The Unum Part 1 yr op A New Number Format: The Unum ht ig 1 Overview l- ia er at M or yl Ta an Fr ci You can t boil the ocean. Former Intel executive, reacting to the idea of unum. Incidentally, the pronunciation

More information

Shortest Path Routing in Arbitrary Networks

Shortest Path Routing in Arbitrary Networks Journal of Algorithm, Vol 31(1), 1999 Shortet Path Routing in Arbitrary Network Friedhelm Meyer auf der Heide and Berthold Vöcking Department of Mathematic and Computer Science and Heinz Nixdorf Intitute,

More information

Lecture 8: More Pipelining

Lecture 8: More Pipelining Overview Lecture 8: More Pipelining David Black-Schaffer davidbb@tanford.edu EE8 Spring 00 Getting Started with Lab Jut get a ingle pixel calculating at one time Then look into filling your pipeline Multiplier

More information

TAM 212 Worksheet 3. The worksheet is concerned with the design of the loop-the-loop for a roller coaster system.

TAM 212 Worksheet 3. The worksheet is concerned with the design of the loop-the-loop for a roller coaster system. Name: Group member: TAM 212 Workheet 3 The workheet i concerned with the deign of the loop-the-loop for a roller coater ytem. Old loop deign: The firt generation of loop wa circular, a hown below. R New

More information

Computer Arithmetic Homework Solutions. 1 An adder for graphics. 2 Partitioned adder. 3 HDL implementation of a partitioned adder

Computer Arithmetic Homework Solutions. 1 An adder for graphics. 2 Partitioned adder. 3 HDL implementation of a partitioned adder Computer Arithmetic Homework 3 2016 2017 Solution 1 An adder for graphic In a normal ripple carry addition of two poitive number, the carry i the ignal for a reult exceeding the maximum. We ue thi ignal

More information

ML85C. Data Sheet. Press fit monitoring module. Special features. Block. diagram PLC. B en

ML85C. Data Sheet. Press fit monitoring module. Special features. Block. diagram PLC. B en ML85C Pre fit monitoring module Special feature Data Sheet Meaurement and evaluation ytem for force/diplacement coure in fitting procee Graphical repreentation of the procee with zoom function Immediate

More information

On combining Learning Vector Quantization and the Bayesian classifiers for natural textured images

On combining Learning Vector Quantization and the Bayesian classifiers for natural textured images On combining Learning Vector Quantization and the Bayeian claifier for natural textured image María Guiarro Dept. Ingeniería del Software e Inteligencia Artificial Facultad Informática Univeridad Complutene

More information

Course Project: Adders, Subtractors, and Multipliers a

Course Project: Adders, Subtractors, and Multipliers a In the name Allah Department of Computer Engineering 215 Spring emeter Computer Architecture Coure Intructor: Dr. Mahdi Abbai Coure Project: Adder, Subtractor, and Multiplier a a The purpoe of thi p roject

More information

Possible application of fractional order derivative to image edges detection. Oguoma Ikechukwu Chiwueze 1 and Alain Cloot 2.

Possible application of fractional order derivative to image edges detection. Oguoma Ikechukwu Chiwueze 1 and Alain Cloot 2. Life Science Journal 3;(4) Poible application of fractional order derivative to image edge detection Oguoma Iechuwu hiwueze and Alain loot. Department of Mathematic and Applied Mathematic Facult of Natural

More information

The Comparison of Neighbourhood Set and Degrees of an Interval Graph G Using an Algorithm

The Comparison of Neighbourhood Set and Degrees of an Interval Graph G Using an Algorithm The Comparion of Neighbourhood Set and Degree of an Interval Graph G Uing an Algorithm Dr.A.Sudhakaraiah, K.Narayana Aitant Profeor, Department of Mathematic, S.V. Univerity, Andhra Pradeh, India Reearch

More information

UNIT -8 IMPLEMENTATION

UNIT -8 IMPLEMENTATION UNIT -8 IMPLEMENTATION 1. Discuss the Bresenham s rasterization algorithm. How is it advantageous when compared to other existing methods? Describe. (Jun2012) 10M Ans: Consider drawing a line on a raster

More information

A note on degenerate and spectrally degenerate graphs

A note on degenerate and spectrally degenerate graphs A note on degenerate and pectrally degenerate graph Noga Alon Abtract A graph G i called pectrally d-degenerate if the larget eigenvalue of each ubgraph of it with maximum degree D i at mot dd. We prove

More information

NUMERICAL MODELING ON THE DAMPING CONTROL OF TLD STRUCTURE

NUMERICAL MODELING ON THE DAMPING CONTROL OF TLD STRUCTURE 4th International Conference on Earthquake Engineering Taipei, Taiwan October 12-13, 2006 Paper No. 183 NUMERICAL MODELING ON THE DAMPING CONTROL OF TLD STRUCTURE Han jun 1, Li Yingmin 2, Liu Liping 3,

More information

Rasterization: Geometric Primitives

Rasterization: Geometric Primitives Rasterization: Geometric Primitives Outline Rasterizing lines Rasterizing polygons 1 Rasterization: What is it? How to go from real numbers of geometric primitives vertices to integer coordinates of pixels

More information

Laboratory Exercise 6

Laboratory Exercise 6 Laboratory Exercie 6 Adder, Subtractor, and Multiplier a a The purpoe of thi exercie i to examine arithmetic circuit that add, ubtract, and multiply number. Each b c circuit will be decribed in Verilog

More information

The Crank-Nicholson method for a nonlinear diffusion equation

The Crank-Nicholson method for a nonlinear diffusion equation > retart; with(plot): with(linearalgebra): with(arraytool): The Crank-Nicholon method for a nonlinear diffuion equation The purpoe of thi workheet i to olve a diffuion equation involving nonlinearitie

More information

Aalborg Universitet. Published in: Proceedings of the Working Conference on Advanced Visual Interfaces

Aalborg Universitet. Published in: Proceedings of the Working Conference on Advanced Visual Interfaces Aalborg Univeritet Software-Baed Adjutment of Mobile Autotereocopic Graphic Uing Static Parallax Barrier Paprocki, Martin Marko; Krog, Kim Srirat; Kritofferen, Morten Bak; Krau, Martin Publihed in: Proceeding

More information

Lecturer: Ivan Kassamakov, Docent Assistants: Risto Montonen and Anton Nolvi, Doctoral

Lecturer: Ivan Kassamakov, Docent Assistants: Risto Montonen and Anton Nolvi, Doctoral Lecturer: Ivan Kaamakov, Docent Aitant: Rito Montonen and Anton Nolvi, Doctoral tudent Coure webpage: Coure webpage: http://electronic.phyic.helinki.i/teaching/optic-06-/ Peronal inormation Ivan Kaamakov

More information

Midterm 2 March 10, 2014 Name: NetID: # Total Score

Midterm 2 March 10, 2014 Name: NetID: # Total Score CS 3 : Algorithm and Model of Computation, Spring 0 Midterm March 0, 0 Name: NetID: # 3 Total Score Max 0 0 0 0 Grader Don t panic! Pleae print your name and your NetID in the boxe above. Thi i a cloed-book,

More information

Modeling of underwater vehicle s dynamics

Modeling of underwater vehicle s dynamics Proceeding of the 11th WEA International Conference on YTEM, Agio Nikolao, Crete Iland, Greece, July 23-25, 2007 44 Modeling of underwater vehicle dynamic ANDRZEJ ZAK Department of Radiolocation and Hydrolocation

More information

Uninformed Search Complexity. Informed Search. Search Revisited. Day 2/3 of Search

Uninformed Search Complexity. Informed Search. Search Revisited. Day 2/3 of Search Informed Search ay 2/3 of Search hap. 4, Ruel & Norvig FS IFS US PFS MEM FS IS Uninformed Search omplexity N = Total number of tate = verage number of ucceor (branching factor) L = Length for tart to goal

More information

Shortest Paths Problem. CS 362, Lecture 20. Today s Outline. Negative Weights

Shortest Paths Problem. CS 362, Lecture 20. Today s Outline. Negative Weights Shortet Path Problem CS 6, Lecture Jared Saia Univerity of New Mexico Another intereting problem for graph i that of finding hortet path Aume we are given a weighted directed graph G = (V, E) with two

More information

Kinematics Programming for Cooperating Robotic Systems

Kinematics Programming for Cooperating Robotic Systems Kinematic Programming for Cooperating Robotic Sytem Critiane P. Tonetto, Carlo R. Rocha, Henrique Sima, Altamir Dia Federal Univerity of Santa Catarina, Mechanical Engineering Department, P.O. Box 476,

More information

Exercise 4: Markov Processes, Cellular Automata and Fuzzy Logic

Exercise 4: Markov Processes, Cellular Automata and Fuzzy Logic Exercie 4: Marko rocee, Cellular Automata and Fuzzy Logic Formal Method II, Fall Semeter 203 Solution Sheet Marko rocee Theoretical Exercie. (a) ( point) 0.2 0.7 0.3 tanding 0.25 lying 0.5 0.4 0.2 0.05

More information

arxiv: v3 [cs.cg] 1 Oct 2018

arxiv: v3 [cs.cg] 1 Oct 2018 Improved Time-Space Trade-off for Computing Voronoi Diagram Bahareh Banyaady Matia Korman Wolfgang Mulzer André van Renen Marcel Roeloffzen Paul Seiferth Yannik Stein arxiv:1708.00814v3 [c.cg] 1 Oct 2018

More information

Points and lines. x x 1 + y 1. y = mx + b

Points and lines. x x 1 + y 1. y = mx + b Points and lines Point is the fundamental element of the picture representation. It is nothing but the position in a plan defined as either pairs or triplets of number depending on whether the data are

More information

A NEW APPROACH IN MEASURING OF THE ROUGHNESS FOR SURFACE CONSTITUTED WITH MACHINING PROCESS BY MATERIAL REMOVAL

A NEW APPROACH IN MEASURING OF THE ROUGHNESS FOR SURFACE CONSTITUTED WITH MACHINING PROCESS BY MATERIAL REMOVAL International Journal of Mechanical and Production Engineering Reearch and Development (IJMPERD) ISSN 49-689 Vol. 3, Iue, Mar 3, 4-5 TJPRC Pvt. Ltd. A NEW APPROACH IN MEASURING OF THE ROUGHNESS FOR SURFACE

More information