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    University of Windsor

    Scholarship at UWindsor

    Electronic Teses and Dissertations

    2011

    FPGA Implementation of Blob RecognitionJian XiongUniversity of Windsor, xiongj@uwindsor.ca

    Follow this and additional works at: hp://scholar.uwindsor.ca/etd

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    Recommended CitationXiong, Jian, "FPGA Implementation of Blob Recognition" (2011).Electronic Teses and Dissertations. Paper 148.

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    FPGA Implementation of Blob Recognition

    by

    Jian Xiong

    A Thesis

    Submitted to the Faculty of Graduate Studiesthrough Electrical and Computer Engineering

    in Partial Fulfillment of the Requirements for

    the Degree of Master of Applied Science at theUniversity of Windsor

    Windsor, Ontario, Canada

    2010

    2010 Jian Xiong

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    FPGA Implementation of Blob Recognition

    by

    Jian Xiong

    APPROVED BY:

    ______________________________________________

    Dr. Xueyuan NieDepartment of Mechanical, Automotive and Materials Engineering

    ______________________________________________Dr. Narayan Kar

    Department of Electrical and Computer Engineering

    ______________________________________________

    Dr. Jonathan Wu, Advisor

    Department of Electrical and Computer Engineering

    ______________________________________________

    Dr. R. Rashidzadeh, Chair of DefenseDepartment of Electrical and Computer Engineering

    November 26, 2010

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    iii

    DECLARATION OF CO-AUTHORSHIP/PREVIOUS

    PUBLICATIONS

    0.1 CO- Authorship Declaration

    I hereby declare that this thesis incorporates material that is result of joint research as

    follows:

    This thesis also incorporates the outcome of a joint research undertaken in

    collaboration with Mr. Thanh Nguyen under the supervision of Professor Jonathan Wu.

    The collaboration is covered in Chapter 3 and 4 of the thesis as the development of the

    PC based software algorithm for this project has been done by Mr. Thanh Nguyen. In all

    rest of the cases, the key ideas, primary contributions, experimental designs, data analysis

    and interpretation, were performed by the author, and the contribution of co-authors was

    primarily through helping in obtaining experimental results presented in section 4.3.

    I am aware of the University of Windsor Senate Policy on Authorship and I certify

    that I have properly acknowledged the contribution of other researchers to my thesis, and

    have obtained written permission from each of the co-author(s) to include the above

    material(s) in my thesis.

    I certify that, with the above qualification, this thesis, and the research to which it

    refers, is the product of my own work.

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    iv

    0.2 Declaration or Previous Publication

    This thesis borrows some of its material from one original paper that has been previously

    published as follows:

    1. Jian Xiong, Q.M. Jonathan Wu, An Investigation of FPGA Implementation for

    Image Processing, ICCCAS.2010

    I certify that I have obtained a written permission from the copyright owner(s) to

    include the above published material(s) in my thesis. I certify that the above material

    describes work completed during my registration as graduate student at the University of

    Windsor.

    I declare that, to the best of my knowledge, my thesis does not infringe upon

    anyones copyright nor violate any proprietary rights and that any ideas, techniques,

    quotations, or any other material from the work of other people included in my thesis,

    published or otherwise, are fully acknowledged in accordance with the standard

    referencing practices. Furthermore, to the extent that I have included copyright material

    that surpasses the bounds of fair dealing within the meaning of the Canada Copyright Act,

    I certify that I have obtained a written permission from the copyright owner(s) to include

    such material(s) in my thesis. I declare that this is a true copy of my thesis, including any

    final revisions, as approved by my thesis committee and the Graduate Studies office, and

    that this thesis has not been submitted for a higher degree to any other University of

    Institution.

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    v

    ABSTRACT

    Real-time embedded vision systems can be used in a wide range of applications

    and therefore the demand has been increasing for them.

    In this thesis, an FPGA-based embedded vision system capable of recognizing

    objects in real time is presented. The proposed system architecture consists of multiple

    Intellectual Properties (IPs), which are used as a set of complex instructions by an

    integrated 32-bit CPU Microblaze. Each IP is tailored specifically to meet the needs of

    the application and at the same time to consume the minimum FPGA logic resources.

    Integrating both hardware and software on a single FPGA chip, this system can achieve

    the real-time performance of full VGA video processing at 32 frames per second (fps). In

    addition, this work comes up with a new method called Dual Connected Component

    Labelling (DCCL) suitable for FPGA implementation.

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    TABLE OF CONTENTS

    DECLARATION OF CO-AUTHORSHIP/PREVIOUS PUBLICATIONS...............iii

    ABSTRACT....................................................................................................................... v

    ACKNOWLEDGEMENTS ............................................................................................ vi

    LIST OF TABLES............................................................................................................ x

    LIST OF FIGURES......................................................................................................... xi

    1 INTRODUCTION.......................................................................................................... 1

    1.1 Problem Statement .................................................................................................... 1

    1.2 Thesis Organization .................................................................................................. 5

    2 REVIEW OF LITERATURE....................................................................................... 7

    2.1 Overview of FPGA Implementation for Image Recognition.................................... 7

    2.2 Algorithm Feature and FPGA Implementation Challenges...................................... 9

    2.3 System Architecture For Video Rate Image Processing......................................... 11

    2.4 FPGA Based Embedded Processor......................................................................... 13

    2.5 IP Designed with System-Level Tools ................................................................... 16

    2.6 Existing FPGA-Based Embedded Vision System .................................................. 18

    3 DESIGN AND METHODOLOGY ............................................................................ 22

    3.1 Board-Level System Architecture........................................................................... 22

    3.2 IP-Level System Architecture................................................................................. 24

    3.3 Peripheral IP Design ............................................................................................... 28

    3.3.1 Image Acquisition IP........................................................................................ 28

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    3.3.2 I2C IP.......................