Learn more about Video and Image Processing Blockset

Version 3.0 (R2010a) Video and Image Processing Blockset

This table summarizes what's new in Version 3.0 (R2010a):

New Features and Changes	Version Compatibility Considerations	Fixed Bugs and Known Problems	Related Documentation at Web Site
Yes Details below	No	Bug Reports Includes fixes	Printable Release Notes: PDF Current product documentation

• New System Objects Provide Video and Image Processing Algorithms for use in MATLAB

• Intel Integrated Performance Primitives Library Support Added to 2-D Correlation, 2-D Convolution, and 2-D FIR Filter Blocks

• Variable Size Data Support

• Expanded From and To Multimedia File Blocks with Additional Video Formats

• New Simulink Demos

• New System Object Demos

• SAD Block Obsoleted

New System Objects Provide Video and Image Processing Algorithms for use in MATLAB

System objects are algorithms that provide stream processing, fixed-point modeling, and code generation capabilities for use in MATLAB programs. These new objects allow you to use video and image processing algorithms in MATLAB, providing the same parameters, numerics and performance as corresponding Video and Image Processing Blockset™ blocks. System objects can also be used in Simulink models via the Embedded MATLAB^® Function block.

Intel Integrated Performance Primitives Library Support Added to 2-D Correlation, 2-D Convolution, and 2-D FIR Filter Blocks

The 2-D Correlation, 2-D Convolution, and 2-D FIR Filter blocks are now taking advantage of SSE Intel instruction set and multi-core processor capabilities for double and single data types.

Variable Size Data Support

Several Video and Image Processing Blockset blocks now support changes in signal size during simulation. The following blocks support variable size data as of this release:

2-D FFT	Hough Transform
2-D FIR Filter	Image Data Type Conversion
Apply Geometric Transformation	Image Pad
Autothreshold	Insert Text
Bottom-hat	Label
Chroma Resampling	Maximum
Closing	Mean
Color Space Conversion	Median
Compositing	Minimum
Contrast Adjustment	Opening
Dilation	Rotate
Edge Detection	Standard Deviation
Erosion	Template Matching
Estimate Geometric Transformation	To Video Display
Find Local Maxima	Top-hat
Frame Rate Display	Variance
Gaussian Pyramid	Video Viewer

See Working with Variable-Size Signals for more information about variable size data.

Expanded From and To Multimedia File Blocks with Additional Video Formats

The To Multimedia File and From Multimedia File blocks now support 4:2:2 YCbCr video formats.

The To Multimedia File block now supports WMV, WMA, and WAV file formats on Windows^® platforms. This block now supports broadcasting WMV and WMA streams over the network.

New Simulink Demos

The Video and Image Processing Blockset contain new and enhanced demos.

New Modeling a Video Processing System for an FPGA Target Demo

This demo uses the Video and Image Processing Blockset™ in conjunction with Simulink HDL Coder™ to show a design workflow for generating Hardware Design Language (HDL) code suitable for targeting video processing application on an FPGA. The demo reviews how to design a system that can operate on hardware.

New System Object Demos

New Image Rectification Demo

This demo shows how to rectify two uncalibrated images where the camera intrinsics are unknown. Rectification is a useful procedure in many computer vision applications. For example, in stereo vision, it can be used to reduce a 2-D matching problem to a 1-D search. This demo is a prerequisite for the Stereo Vision demo.

New Stereo Vision Demo

This demo computes the depth map between two rectified stereo images using block matching, which is the standard algorithm for high-speed stereo vision in hardware systems. It further explores dynamic programming to improve accuracy, and image pyramiding to improve speed.

New Video Stabilization Using Point Feature Matching

This demo uses a point feature matching approach for video stabilization, which does not require knowledge of a feature or region of the image to track. The demo automatically searches for the background plane in a video sequence, and uses its observed distortion to correct for camera motion. This demo presents a more advanced algorithm in comparison to the existing Video Stabilization demo in Simulink.

SAD Block Obsoleted

The new Template Matching block introduced in the previous release, supports Sum of Absolute Differences (SAD) algorithm. Consequently, the SAD Block has been obsoleted.

Video and Image Processing Blockset Release Notes

Version 2.8 (R2009b) Video and Image Processing Blockset

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