Image Processing. Ch1: Introduction. Prepared by: Hanan Hardan. Hanan Hardan 1

Transcription

1 Processing Ch1: Introduction Prepared by: Hanan Hardan Hanan Hardan 1

2 Introduction One picture is worth more than ten thousand words Hanan Hardan 2

3 References Digital Processing, Rafael C. Gonzalez & Richard E. Woods, Addison-Wesley, 2002 Much of the material that follows is taken from this book Machine Vision: Automated Visual Inspection and Robot Vision, David Vernon, Prentice Hall, 1991 Hanan Hardan 3

4 Contents This lecture will cover: What is a digital image? What is digital image processing? State of the art examples of digital image processing Key stages in digital image processing Hanan Hardan 4

5 What is a Digital? A digital image: is a representation of a two-dimensional image as a finite number of elements, each one has a particular location and value.. These element are called picture elements, image elements or pixels. Hanan Hardan 5

6 What is a Digital? (cont ) Pixels: Elements of the digital image, each has intensity. Intensity of pixel: the amplitude غزارة of gray level (in gray scale images) 1 pixel Hanan Hardan 6

7 What is digital? Hanan Hardan 7

8 What is digital? An image can be defined as function of 2 variables, f(x,y), where x and y are spatial coordinates, and the amplitude of f at any pair of coordinates (x, y) is called the intensity of the image at that point Hanan Hardan 8

9 What is digital image? The image consists of finite number of pixels ( f(x,y) ) Every pixel Is an intersection between a row and a column. Every pixel has intensity pixel Ex: f(2,6)= 123 Refers to a pixel existing on the intersection between row 2 with column 6, and its intensity is 123. Remember digitization implies that a digital image is an approximation of a real scene Hanan Hardan 9

10 Digital image processing focuses on two major tasks Improve image quality(pictorial information) for human perception and interpretation Processing of image data for storage, transmission and representation for autonomous machine perception Hanan Hardan 10

11 processing fields: 1. Computer Graphics: the creation of image 2. processing: enhancement or other manipulation of the image 3. Computer vision: analysis of the content Hanan Hardan 11

12 What are digital image processing levels? low level processes: Input and output are images Tasks: Primitive operations, such as, image processing to reduce noise, contrast enhancement and image sharpening مثال صورة قديمة نريد تحسينها Hanan Hardan 12

13 What are digital image processing levels? Mid-Level Processes: Inputs, generally, are images. Outputs are attributes extracted from those images (edges, contours, identity of individual objects) Tasks: Segmentation (partitioning an image into regions or objects) Description of those objects to reduce them to a form suitable for computer processing Classifications (recognition) of objects مثال: صورة لكرسي نريد تعديلها حاسوبيا لنبرز حوافه Hanan Hardan 13

14 What are digital image processing levels? High-Level Processes Input: Attributes Output: Understanding Tasks: recognizing objects analysis and computer vision(analysis of the image content) Examples: Scene understanding مثال: صورة لمشتبه فيه نريد الحاسوب ان يتعرف عليه Hanan Hardan 14

15 Uses of DIP enhancement/restoration Artistic effects Medical visualisation Law enforcement Human computer interfaces Hanan Hardan 15

16 Examples: Enhancement One of the most common uses of DIP techniques: improve quality, remove noise etc Hanan Hardan 16

17 Examples: The Hubble Telescope Launched in 1990 the Hubble telescope can take images of very distant objects However, an incorrect mirror made many of Hubble s images useless processing techniques were used to fix this Hanan Hardan 17

18 Examples: Artistic Effects Artistic effects are used to make images more visually appealing, to add special effects and to make composite images Hanan Hardan 18

19 Examples: Medicine Take slice from MRI (Magnetic Resounance Imaging) scan of a heart, and find boundaries between types of tissue with gray levels representing tissue density Use a suitable filter to highlight edges Hanan Hardan 19

20 Examples: GIS Geographic Information Systems Digital image processing techniques are used extensively to manipulate satellite imagery (التضاريس) Terrain classification (األرصاد الجوية) Meteorology Hanan Hardan 20

21 Examples: Law Enforcement processing techniques are used extensively by law enforcers Number plate recognition for speed cameras Fingerprint recognition Hanan Hardan 21

22 Examples: HCI Try to make human computer interfaces more natural Face recognition Hanan Hardan 22

23 Fundamental steps in digital image processing Hanan Hardan 23

24 1. Acquisition: (capturing an image in digital form) Restoration Morphologic al Processing Enhancemen t Segmentatio n Acquisition Object Recognition Problem Domain Colour Processing Representatio n & Description Hanan Hardan Compression 24

25 2. Enhancement: making an image look better in a subjective way. Restoration Morphologic al Processing Enhancemen t Segmentatio n Acquisition Object Recognition Problem Domain Colour Processing Representatio n & Description Hanan Hardan Compression 25

26 3. Restoration: improving the appearance of any image objectively. Restoration Morphologic al Processing Enhancemen t Segmentatio n Acquisition Object Recognition Problem Domain Colour Processing Representatio n & Description Hanan Hardan Compression 26

27 4.Morphological Processing: extracting image components that are useful in the representation and description of shape Restoration Morphologic al Processing Enhancemen t Segmentatio n Acquisition Object Recognition Problem Domain Colour Processing Representatio n & Description Hanan Hardan Compression 27

28 5.Segmentation: partitioning an image into its constituent parts or objects. Restoration Morphological Processing Enhancemen t Segmentation Acquisition Object Recognition Problem Domain Colour Processing Representatio n & Description Hanan Hardan Compression 28

29 6.Object Recognition: assigning a label to an object based on its descriptors Restoration Morphologic al Processing Enhancemen t Segmentatio n Acquisition Object Recognition Problem Domain Colour Processing Representatio n & Description Hanan Hardan Compression 29

30 7.Representation & Description: boundary representation vs. region representation. Boundary descriptors vs. region descriptors Restoration Morphologic al Processing Enhancemen t Segmentatio n Acquisition Object Recognition Problem Domain Colour Processing Representatio n & Description Hanan Hardan Compression 30

31 8. Compression: reducing the stored and transmitted image data. Restoration Morphologic al Processing Enhancemen t Segmentatio n Acquisition Object Recognition Problem Domain Colour Processing Representatio n & Description Hanan Hardan Compression 31

32 9.Colour Processing: color models and basic color processing Restoration Morphologic al Processing Enhancemen t Segmentatio n Acquisition Object Recognition Problem Domain Colour Processing Representatio n & Description Hanan Hardan Compression 32