Book Image

Rapid BeagleBoard Prototyping with MATLAB and Simulink

Book Image

Rapid BeagleBoard Prototyping with MATLAB and Simulink

Overview of this book

As an open source embedded single-board computer with many standard interfaces, Beagleboard is ideal for building embedded audio/video systems to realize your practical ideas. The challenge is how to design and implement a good digital processing algorithm on Beagleboard quickly and easily without intensive low-level coding. Rapid BeagleBoard Prototyping with MATLAB and Simulink is a practical, hands-on guide providing you with a number of clear, step-by-step exercises which will help you take advantage of the power of Beagleboard and give you a good grounding in rapid prototyping techniques for your audio/video applications. Rapid BeagleBoard Prototyping with MATLAB and Simulink looks at rapid prototyping and how to apply these techniques to your audio/video applications with Beagleboard quickly and painlessly without intensive manual low-level coding. It will take you through a number of clear, practical recipes that will help you to take advantage of both the Beagleboard hardware platform and Matlab/Simulink signal processing. We will also take a look at building S-function blocks that work as hardware drivers and interfaces for Matlab/Simulink. This gives you more freedom to explore the full range of advantages provided by Beagleboard. By the end of this book, you will have a clear idea about Beagleboard and Matlab/Simulink rapid prototyping as well as how to develop voice recognition systems, motion detection systems with I/O access, and serial communication for your own applications such as a smart home.
Table of Contents (15 chapters)
Rapid BeagleBoard Prototyping with MATLAB and Simulink
Credits
About the Authors
About the Reviewers
www.PacktPub.com
Preface
Index

Implementation algorithm in Simulink


So far, we have explored the basic idea of a motion detection algorithm. In this section, we show how to detail and implement this algorithm in Simulink, and deploy it to the BeagleBoard step by step.

Grayscale image

The first issue is regarding the color space. Since a frame with RGB color space contains redundant information in three colors, we implement the motion detector algorithm in monochrome to save computation cost. We first convert the frame data from RGB color space into the grayscale format with the Color Space Conversion block, which can be found in the Computer Vision System toolbox. Let's drag this Color Space Conversion block into our minimum system, and double-click on the icon to configure the conversion mode into RGB to intensity mode and the image signal into separate color signals through the dropdown selection. After the processing of this block, the frame data has been converted from [160,120,3] into a simpler two-dimension matrix...