Steve on Image Processing with MATLAB

Image processing concepts, algorithms, and MATLAB

Computer Vision System Toolbox in R2011a

Some of you may have already noticed a new product in R2011a: Computer Vision System Toolbox. You may also have noticed that Video and Image Processing Blockset disappeared! These are not unrelated, as we took the blockset, added new computer vision algorithms, and changed the name to Computer Vision System Toolbox. Here’s a list of what’s new:

  • extractFeatures function for creating an array of feature vectors (descriptors) based on interest points within an image
  • matchFeatures function for finding the best matches between two arrays of feature vectors (descriptors)
  • Visualization of epipolar geometry for stereo images using epipolarLine, isEpipoleInImage, and lineToBorderPoints functions
  • estimateUncalibratedRectification function for calculating projective transformations to rectify stereo images
  • Video segmentation based on Gaussian Mixture Models using ForegroundDetector System object
  • YCbCr video format support for ToVideoDisplay block and DeployableVideoPlayer System object

Calling this product a toolbox also allows us to clarify and highlight the MATLAB capabilities in the product that we’ve had since R2010a. Some of these algorithms overlap with Image Processing Toolbox, but provide support for C code generation and fixed-point modeling. Others are unique to Computer Vision System Toolbox, including these:

  • vision.BlockMatcher
  • vision.Deinterlacer
  • vision.GeometricTransformEstimator
  • vision.OpticalFlow
  • vision.TemplateMatcher

So, now we have one product for use in both MATLAB and Simulink that supports the design and simulation of computer vision and video processing systems. It contains MATLAB functions, MATLAB System objects, and Simulink blocks. You can learn more about these capabilities by looking at the documentation for Computer Vision System Toolbox.

Published with MATLAB® 7.12

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