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| Documentation → Video and Image Processing Blockset |
| Contents | Index |
| Learn more about Video and Image Processing Blockset |
This table summarizes what's new in Version 2.6 (R2008b):
| New Features and Changes | Version Compatibility Considerations | Fixed Bugs and Known Problems | Related Documentation at Web Site |
|---|---|---|---|
| Yes Details below | Yes Summary | Bug
Reports Includes fixes | Printable Release Notes: PDF Current product documentation |
New features and changes introduced in this version are:
The Apply Geometric Transformation block can be used to transform an image using a projective, affine or non-reflective similarity transformation matrix. The block provides Polygon ROI support supplied manually or calculated using segmentation and trace boundary techniques. This block used together with the Estimate Geometric Transformation block provides a flexible, robust model to transform images.
C code generation and the Simulink Accelerator and Rapid Accelerator modes are now supported for fixed-point and integer word lengths up to 128 bits. The few exceptions where Real-Time Workshop® Embedded Coder™ will not generate code for fixed-point and integer word lengths beyond 32 bits are for the Autothreshold, Histogram Equalization, Hough Lines, Projective Transformation, and Shear blocks.
Full Region of Interest (ROI) support is available for the Minimum and Maximum blocks. Use the ROI type parameter to specify whether the ROI is a rectangle, line, label matrix, or binary mask. Full ROI processing is available to users who have a Video and Image Processing Blockset™ license. If you only have a Signal Processing Blockset™ license, you can still use ROI processing, but are limited to the ROI type Rectangles.
The Video and Image Processing Blockset contain new and enhanced demos.
Two new demos using the Video and Image Processing Blockset to create an image processing system which can recognize and interpret a GTIN-13 barcode. The GTIN-13 barcode, formally known as EAN-13, is an international barcode standard. It is a superset of the widely used UPC standard.
The live video demo uses the From Video Device block provided by Image Acquisition Toolbox™ to acquire live image data from a Unibrain Fire-i digital camera into Simulink.
This demo detects and tracks road lane markers in a video sequence and notifies the driver if they are moving across a lane. The demo illustrates how to use the Hough Transform, Hough Lines and Kalman Filter blocks from the Video and Image Processing Blockset blocks to create a line detection and tracking algorithm.
The enhanced version of the demo uses a virtual reality scene as the input. The demo provides the user with an example of using the Virtual Reality Toolbox™.
The Video and Image Processing Blockset Data Type Support Table is now available through the Simulink model Help menu. The table provides information about data type support and code generation coverage for all Video and Image Processing Blockset blocks. Select Help > Block Support Table> Video and Image Processing Blockset or Help > Block Support Table > All Tables. You can also type showvipblockdatatypetable at the MATLAB command line to bring up the table.
The Skip divide-by-two on butterfly outputs for fixed-point signals check box on the Fixed-point pane of the 2D-FFT block dialog has been moved to the Main pane and renamed Divide butterfly outputs by two. This check box now correctly applies to both fixed-point and floating-point inputs. In releases prior to R2008b, the block always ignored this check box for floating-point inputs.
The 2D-FFT block can give results in R2008b and later releases that are scaled differently than in previous releases when all the following conditions are met:
The block input is floating point.
The Divide butterfly outputs by two check box is selected (or the Skip divide-by-two on butterfly outputs for fixed-point signals check box on the ‘Fixed-point' pane was NOT selected, for releases prior to R2008b)
The Logging mode parameter on the Fixed-Point Tool for the model is not set to Minimums, maximums and overflows
Make sure that this check box is set correctly for your needs. Refer to the block reference page for more information.
When using Constant padding, the block now ensures that the pad value is real when the input image is real.
You will get an error message if pad value is complex when the input is real.
To build a model that pads a real input with a complex value, you can use the Bias block to add a complex zero value.
 | Version 2.7 (R2009a) Video and Image Processing Blockset | Version 2.5 (R2008a) Video and Image Processing Blockset |  |
Learn more about Simulink through this collection of videos, articles, technical literature and the Getting Started with Simulink Guide.
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