Version 2.0 (R14SP3+) Video and Image Processing Blockset™ Release Notes

Version 2.0 (R14SP3+) Video and Image Processing Blockset

This table summarizes what's new in Version 2.0 (R14SP3+):

New features and changes introduced in this version are

Blocks Added

Block Matching

Use the Block Matching block to estimate motion between images or video frames.

Deinterlacing

Use the Deinterlacing block to remove motion artifacts by deinterlacing the input video signal.

Gaussian Pyramid

Use the Gaussian Pyramid block to perform Gaussian pyramid decomposition.

Optical Flow

Use the Optical Flow block to estimate object velocities.

Projective Transformation

Use the Projective Transformation block to transform a quadrilateral into another quadrilateral.

PSNR

Use the PSNR block to compute the peak signal-to-noise ratio (PSNR) between two images.

Block Enhancements

2-D Mean, 2-D Standard Deviation, and 2-D Variance

The 2-D Mean, 2-D Standard Deviation, and 2-D Variance blocks let you compute the statistic value over a particular region of interest (ROI).

Blob Analysis

The Blob Analysis block lets you calculate the perimeter of blobs.

Color Space Conversion

The Color Space Conversion block lets you specify the standard to use for conversions between R'G'B' and Y'CbCr color spaces. Your choices are Rec. 601 (SDTV) or Rec. 709 (HDTV).

Compositing, Image Data Type Conversion, Median Filter, and SAD

The Compositing, Image Data Type Conversion, Median Filter, and SAD blocks accept Boolean data types on their input ports.

MPlay

The mplay GUI has been enhanced, so it is easier to use and has greater capabilities.

Demos Added

Projecting Videos onto a Rotating Cube

You can find this demo in the Geometric Transformation library. Open the demo model by typing viprm at the MATLAB command prompt.

Tracking Cars Using Optical Flow

You can find this demo in the Detection and Tracking library. Open the demo model by typing viptrafficof at the MATLAB command prompt.

Traffic Warning Sign Recognition

You can find this demo in the Detection and Tracking library. Open the demo model by typing vipwarningsigns at the MATLAB command prompt.

Demo Enhancements

Periodic Noise Reduction

You can find this demo in the Video Enhancement library. Open the demo model by typing vipstripes at the MATLAB command prompt. This demo now includes a frequency domain filtering technique.

Version 2.1 (R2006a) Video and Image Processing Blockset

Version 1.2 (R14SP3) Video and Image Processing Blockset