Image Analysis Using MATLAB

Transcription

1 Image Analysis Using MATLAB Vatsal Sanjay, Akash Deep and Dr. Arup Kumar Das Department of Mechanical and Industrial Engineering, Indian Institute of Technology, Roorkee, India Abstract We have presented here the details (compilation) of image analysis carried out under on experimental and numerical output images and videos. The best thing about images is that they are simply matrices whereby the pixel size (mxn) is simply the rows m and columns n. The best way to manipulate matrices is to use matlab. In a given image, pixel size denotes the size of matrix. In case of a binary image, in addition to the location of a given pixel (and hence the cell of that matrix), the value stored there is an integer: 1 or 0; 1 for white and 0 for black. In case of a colored image the value stored is a vector [RGB] which has different combinations for different colors. Contents 1 Movie to frames 1 2 Frames to Movie 2 3 Image Processing of a single image 5 4 Calculation of Area 8 5 Calculation of Perimeter 8 6 Calculation of centroid 9 7 Image Processing of multiple frames 10 1 Movie to frames Just run the following code with customized name of video in filename and folder where you wish to store the images (frames). clc; close all; clear all; assigning the name of sample video file to a variable, eg : new.avi filename = Name of video file ; reading a video file mov = VideoReader(filename); Defining Output folder as snaps opfolder = fullfile(cd, snaps ); if not existing if ~exist(opfolder, dir ) make directory & execute as indicated in opfolder variable mkdir(opfolder); getting no of frames numframes = mov.numberofframes; setting current status of number of frames written to zero numframeswritten = 0; for loop to traverse & process from frame 1 to last frames 1

2 for t = 1 : numframes currframe = read(mov, t); reading individual frames opbasefilename = sprintf( 3.3d.png, t); opfullfilename = fullfile(opfolder, opbasefilename); imwrite(currframe, opfullfilename, png ); saving as png file indicating the current progress of the file/frame written progindication = sprintf( Wrote frame 4d of d., t, numframes); disp(progindication); numframeswritten = numframeswritten + 1; of for loop progindication = sprintf( Wrote d frames to folder "s",numframeswritten, opfolder); disp(progindication); End of the code clear all 2 Frames to Movie Please be very careful with the nomenclature of the frames used. It is advisable to have a frame named 0119.png instead of 119.png in case you you have more than 999.png images. Triggering command: imagefolder2mpeg( name_of_folder_with_all_snaps ) image folder to mpeg EXAMPLES Simple call: >> imagefolder2mpeg( exampleimages ) Set frame rate: >> imagefolder2mpeg( exampleimages, framerate,30) Only export images 1 through 10 >> imagefolder2mpeg( exampleimages, numstoexport,1:10) Todd Karin 09/04/2013 function imagefolder2mpeg(foldername,varargin) Do some validity checking on param-value pairs parampairs = varargin; if (rem(length(parampairs),2) ~= 0) error([ Invalid input syntax. Optional parameters and values... must be in pairs. ]); Default param values framerate = 10; quality = 100; numstoexporton = 0; moviefname = [foldername.mp4 ]; Process param-value pairs for k = 1:2:length(paramPairs) param = lower(parampairs{k}); if (~ischar(param)) error( Optional parameter names must be strings ); 2

3 value = parampairs{k+1}; switch (param) case framerate framerate = value; case quality quality = value; case numstoexport numstoexporton = 1; numstoexport = value; case moviefname moviefname = value; otherwise error( Option not recognized ) Get all the file names in the folder fnames = getallfilesinfolder(foldername); N = length(fnames); disp([ Found num2str(n) images ]) Set up video writer object writerobj = VideoWriter(movieFname, MPEG-4 ); set(writerobj, FrameRate,frameRate,... Quality,quality) disp( Writer object parameters: ) get(writerobj) open(writerobj); if ~numstoexporton numstoexport=1:n; N = length(numstoexport); disp([ Number of images to export: num2str(n) 10 10]) disp( Running Export... ) Read in and export the images. Print time elapsed tic tlast=0; disp([ Percent Done () 9 Time Remaining (s) ]); for j=numstoexport Write the video writevideo(writerobj, imread( fullfile(foldername, fnames{j})) ); print out progress tnow=toc; if tnow>tlast+1 tlast = tlast+.5; disp([ Percent Done: num2str(100*j/n, 2.2f ) 9 9 Time Remaining: num2str(tnow/j*ndisp([ num2str(100*j/n, 2.2f ) 9 9 num2str(tnow/j*n-tnow, 2.1f ) ]); disp([10 Done! Elapsed time: num2str(toc,2) s ]) close(writerobj); 3

4 Get all files in the folder GETALLFILESINFOLDER - Returns all non-hidden files in a given folder Todd Karin 10/11/2013 function fname = getallfilesinfolder(foldername) finfo = dir(foldername); j=1; if length(finfo)>2 for i=1:length(finfo) fnamecurr = finfo(i).name; if fnamecurr(1)~=. Extract the filename fname{j} = fnamecurr; j=j+1; 4

5 3 Image Processing of a single image Start assign output folder Image background image Subtract the image from background region not crop change to grayscale Contrast not adjust the contrast enhance the image Centroid Claculation (Section 6) convert to BW image Area Claculation (Section 4) remove small patches Perimeter Claculation(Section 5) track the edge Colour not invert image output processed image Stop 5

6 Please note that the decisions involved in this section are to be carried out manually. You need to select one of the images from the sequence and see which values of pixel region, contrast and color suit the purpose. Since, these parameters are mainly depent on the lighting involved while taking the images, no generalization can be done. Once one of the images are customized, just run the loop (see the section 7). For contour (edge tracking), in-build methods are pre-built in MATLAB. So, we have not included the details here. clear all; close all; clc; opfolder = fullfile(cd, output ); if not existing if ~exist(opfolder, dir ) make directory & execute as indicated in opfolder variable mkdir(opfolder); im=imread( image_name.format ); name of image with format. eg- original.jpg im=imcrop(im,[ ]); crop if required im=imrotate(im,90); rotate if required imwrite(im,fullfile(opfolder, original.png ), png ); im=imrotate(im,-90); rotate if required b=imread( background.format ); back ground image b=imcrop(b,[ ]); crop if required im=b-im; subtract image from back ground im=rgb2gray(im); to grayscale im=imadjust(im, [0.15;0.44], []); adjusting the contrast im=imrotate(im,90); imwrite(im,fullfile(opfolder, gray.png ), png ); im=imfill(im); filling the blanks imwrite(im,fullfile(opfolder, fill.png ), png ); im=im2bw(im,graythresh(im)); convert to black and white optimised imwrite(im,fullfile(opfolder, bw.png ), png ); im=bwareaopen(im,5000); remove small patches imwrite(im,fullfile(opfolder, patchfree.png ), png ); im=edge(im, sobel ); edge tracing imwrite(im,fullfile(opfolder, edge.png ), png ); im=invertim(im); make the outline black imwrite(im,fullfile(opfolder, final.png ), png ); imshow(im) InvertIm Written by Stead Kiger, Ph.D. Department of Radiation Oncology Beth Israel Deaconess Medical Center Harvard Medical School Boston, MA function [invim]=invertim(im, varargin) Initialize parameters bitsstored=[]; lowerlimit=[]; upperlimit=[]; Assign and check optional arguments for parameters error(nargchk(1, 4, nargin, struct )) bitsstored if nargin >= 2, bitsstored=varargin{1}; if ~(isnumeric(bitsstored) isempty(bitsstored)), error( Optional argument bitsstored must be either numeric or empty. ) 6

7 lowerlimit if nargin >= 3, lowerlimit=varargin{2}; if ~(isnumeric(lowerlimit) isempty(lowerlimit)), error( Optional argument lowerlimit must be either numeric or empty. ) upperlimit if nargin == 4, upperlimit=varargin{3}; if ~(isnumeric(upperlimit) isempty(upperlimit)), error( Optional argument upperlimit must be either numeric or empty. ) Check that the image array is either numeric or logical if ~(islogical(im) isnumeric(im)), error( Input array must be logical or numeric, but is s,class(im)) if islogical(im), logical - just apply not invim=~im; else determine the image class, i.e., data type; e.g., uint8, int16 etc. imclass=class(im); create the function handle for casting the double precision image back into its original class clshdl=str2func(imclass); if isinteger(im), get the minimum integer minval=double(intmin(imclass)); if ~isempty(lowerlimit), minval=double(max(minval, lowerlimit)); get the maximum integer maxval=double(intmax(imclass)); if ~isempty(bitsstored), maxval=double(min(maxval, 2^bitsStored - 1)); if ~isempty(upperlimit), maxval=min(maxval, upperlimit); elseif isfloat(im) immin=min(im(:)); immax=max(im(:)); if immin >= 0 && immax <= 1, Intensity image or RGB minval=0; maxval=1; else minval=immin; maxval=immax; 7

8 if ~isempty(lowerlimit), minval=lowerlimit; if ~isempty(upperlimit), maxval=upperlimit; else error( Input array must be logical or numeric, but is s,class(im)) Compute the inverse and cast the array back into its original class invim = feval(clshdl, (maxval + minval) - double(im)); Figure 1: Interface tracking methodology 4 Calculation of Area We are assuming that the interior area (which we have to calculate is white, non zero index at a given pixel location). In case we have to calculate the area of black region, we can do so by either inverting the image or by calculating the number of zero index pixel instead of non-zero index pixels. Start 5 BW image Number of white pixels Multiply by scale Stop Calculation of Perimeter Once you have the tracked edge of the figure, you can simply calculate the number of pixels in black - pixels with index zero (provided the edge is black) or number of pixels in white - pixels with non-zero index (provided the edge is in white) and multiply it by the scale of image. We assume white interface in flowchart Start Edge traced image Number of white pixels Multiply by scale Stop 8

9 6 Calculation of centroid Start BW image counter = 0; x = 0; y = 0 row = 1 Stop yes x row exhausted x = counter and ȳ = y counter no column = 1 row = row + 1 yes column exhausted no zero index column = column + 1 non - zero counter = counter + 1; y = y + row ; x = x + column 9

10 Function for Center of Mass (or centroid coordinates) function [ x, y ] = COM( im ) UNTITLED7 Summary of this function goes here Detailed explanation goes here counter = 1; x=0; y=0; [l, m] = size(im); for i=1:l; for j=1:m; if im(i,j)==1 counter=counter+1; x= x+j; y= y+i; x=x/counter; y=y/counter; 7 Image Processing of multiple frames Just apply a loop for all the images. Here we have given a sample code for the calculation of centroid coordinate and area enclosed for bubble entrainment by a plunging liquid jet impinged onto a liquid pool. clear all; close all; clc; opfolder = fullfile(cd, modified ); if not existing if ~exist(opfolder, dir ) make directory & execute as indicated in opfolder variable mkdir(opfolder); f = OutputExcelFile.xls ; n1= 225; first frame n2=2030; last frame k = (n2-n1)+1; t=linspace(0,9.616*(n2-n1+1)/2035,k); temporal variation based on fps and time scale t=t ; P = zeros(k,1); count=1; X=zeros(k,1); Y=zeros(k,1); A=zeros(k,1); h=zeros(k,1); ref = 9.5*10^-4; Image Scale m per scale for n=n1:1:n2 name = sprintf( 6.6d.bmp, n); a = imread(name); first image read b=imread( bmp ); background a=imadjust(a, [0.4;0.5], []); adjusting the contrast b=imadjust(b, [0.4;0.5], []); adjusting the contrast a=im2bw(a,graythresh(a)); b=im2bw(b,graythresh(b)); im=b-a; background subtracted from image one im=imcrop(im,[ ]); crop if necessary im=imfill(im); filling the blanks im=im2bw(im,graythresh(im)); convert to black and white optimised 10

11 this if else statement is customised and need to be changed if required if r>k/10 im=bwareaopen(im,5000); remove small patches else im=bwareaopen(im,500); imshow(im) [X(count),Y(count)]= COM( im); A(count)= nnz(im); im=edge(im, sobel ); edge tracing P(count)=nnz(im); Perimeter count=count+1; im=invertim(im); make the outline black opbasefilename = sprintf( 6.6d.png, n); opfullfilename = fullfile(opfolder, opbasefilename); imwrite(im, opfullfilename, png ); progindication = sprintf( Wrote frame 4d., (n-n1)/r); disp(progindication); Af=ref*ref*A; Pf=ref*P; Xf=ref*(X-size(im,2)/2); shift origin to center Yf=ref*Y; data= [t Xf Yf Pf Af]; xlswrite(f, data); xlswrite(f, { time x y p A }); 11