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Image and Video Processing in MATLAB

Image and Video Processing in MATLAB. Partly based on slides by Dmitri Roduy. Topics. Data Types Image Representation Image/Video I/O Matrix access Image Manipulation Application: Bright Cars Detection in Video. Image Data Types. Relevant data types

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Image and Video Processing in MATLAB

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  1. Image and Video Processing in MATLAB Partly based on slides by Dmitri Roduy

  2. Topics • Data Types • Image Representation • Image/Video I/O • Matrix access • Image Manipulation • Application: Bright Cars Detection in Video

  3. Image Data Types • Relevant data types • uint8 – [0 255] – native for natural images • uint16 – [0 65,535] – common for medical images • Logical – [0 1] – native for masks, morph. elements • double – 64bit floating point (default range [0 1]) • single – when you want to save memory (32bit floating point) • Simple casting: double(), uint8(). • Type Conversion (of images): • im2double(),im2single(),im2uint8(), im2unit16() • Works for colors, gray-scale, logical images

  4. Common problem I = imread(‘pears.png'); I2 = I-1.4; diffI = I-I2; fprintf('Max difference between images: %d\n',max(diffI(:))); figure(1); subplot(1,2,1); imshow(I); title('I'); subplot(1,2,2); imshow(I2); title('I2');

  5. Common problem I = double(imread('pears.png')); I2 = I-1.4; diffI = I-I2; fprintf('Max difference between images: %2.1f\n',max(diffI(:))); figure(1); subplot(1,2,1); imshow(I); title('I'); subplot(1,2,2); imshow(I2); title('I2');

  6. Possible Solution I = double(imread('pears.png')); I2 = I-1.4; diffI = I-I2; fprintf('Max difference between images: %2.1f\n',max(diffI(:))); figure(1); subplot(1,2,1); max_I= 255; imshow(I/max_I); title('I'); subplot(1,2,2); imshow(I2/max_I); title('I2');

  7. Image Representation 2D Matrix • Intensity: Each pixel value in the dynamic range [minP, maxP]. • Can represent a grayscale image, results of a 2d function etc. • Useful commands: imshow (), imagesc(), colormap(). • Binary: a.k.a masks. • Can represent areas of interest in image, morphological structuring elements and more… • Useful commands: bwlabel(),bwmorph(),bwdist(),im2bw(),bwperim().

  8. Image Representation 3D Matrix • True Color: Three 2D matrices stacked. Each represents a color component. (e.g. RGB) • Can represent an RGB color image, Ycbcr image, LAB image, etc. • Useful commands: imshow(),rgb2gray(),rgb2ycbcr(), ycbcr2rgb(), rgb2lab().

  9. Image/Video I/O Useful Commands • imread() – read image • imwrite() – write image • im2frame() – convert image to movie frame • movie2avi() – write avi file • aviread() – read avi file • mmreader()/VideoReader() – read video (better) • VideoWriter() – create video file (2011b+) • movie() – show movie • implay() – show video interactively

  10. Matrix access Useful Commands: • sub2ind()– convert subscript (e.g. (r,c,clr)) to index (n). • ind2sub() – convert index (n) to subscipt (e.g. (r,c,clr)). • meshgrid() – generate X,Y grids.

  11. Image Manipulation Useful Functions: • imrotate()– Rotate image. • imfilter() – Use kernal to convolve/correlation. • nlfilter() – Sliding neighborhood operation. • blkproc() – Perform function on (semi-)distinct blocks. • fspecial() – Create common image filter kernels. • imresize() – scale up/down image using defined interpolation. • padarray() – Pad image. • colfilt() – Column-stack filtering (faster) • Many more – see IP toolbox help

  12. Application: Bright Cars Detection in Video • Objective: Tag with a red square bright colored cars in a color video with moving cars. • Stages: • Convert each RGB frame to gray scale. • Search for regional maximas above a brightness threshold • Remove small regions (i.e morphology) • Compute centroid of each region • Place a red square in centroid location • Repeat 1-5 for all video frames

  13. Morphological Open Erosion of the image with the Structuring Element followed by Dilation of the image with the Structuring Element.

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