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Student Number 965201035
Author De-Zhang Peng(´^¼w¹ü)
Author's Email Address zack911451@dsp.ee.ncu.edu.tw
Statistics This thesis had been viewed 1288 times. Download 367 times.
Department Electrical Engineering
Year 2008
Semester 2
Degree Master
Type of Document Master's Thesis
Language English
Title VLSI Design for Foreground Object Segmentation with Labeling and Noise Reduction Mode in Video Surveillance Application
Date of Defense 2009-07-09
Page Count 91
Keyword
  • Video Segmentation
  • Video Surveillance Application
  • VLSI
  • Abstract In computer vision applications, such as video surveillance, human-machine interaction and object based video compression standard (e.g., MPEG-4), most applications attempt to detect, recognize events and tracking foreground objects. There also have many real-time applications. The foreground objects segmentation result will do great influence to later process. Therefore how to reduce a foreground objects segmentation result noise effect is very important. In many video surveillance application need to transform image into a symbolic image to do later post-process (e.g., tracking and recognize).
    By above-mentioned requisitions, this paper proposed VLSI design for real-time foreground object segmentation with labeling and noise reduction mode. Our proposed VLSI design has high throughput rate that can meet the high resolution specification (e.g., HD720P) with real-time requirement and low cost design. In this paper system consists three parts. First, a foreground objects segmentation architecture design with multi-model background maintenance algorithm is proposed to segment video image. Second, morphological operation noise reduction architecture is proposed to reduce segmentation result noise. Finally, object labeling architecture is proposed to label noiseless image. In this paper proposed systems is implementation by cell-base design flow digital VLSI in TSMC 0.18um.
    Table of Content ºK   ­n...I
    ABSTRACT...II
    CONTENT...IV
    LIST OF FIGURES...VI
    LIST OF TABLES...VIII
    CHAPTER 1 INTRODUCTION...1
    1.1INTRODUCTION...2
    1.2THESIS ORGANIZATION...5
    CHAPTER 2 BACKGROUND AND RELATIVE RESEARCH...6
    2.1RELATIVE RESEARCH OF SEGMENTATION ALGORITHM...7
    2.1.1 Nonparametric Approach...8
    2.1.2 Parametric Approach...10
    2.2 RELATIVE RESEARCH OF SEGMENTATION ARCHITECTURE...12
    CHAPTER 3...14
    PROPOSED MULTI-MODEL BACKGROUND MAINTENANCE ALGORITHM...14
    3.1OVERVIEW OF PROPOSED ALGORITHM...15
    3.1.1 Design Strategy...15
    3.1.2 Flowchart of Proposed Algorithm...17
    3.2BACKGROUND MAINTENANCE...18
    3.2.1 Change Classification...19
    3.2.2 Learning and Updating for Dynamic Change...20
    3.2.3 Learning and Updating for Static Point...21
    3.3FOREGROUND EXTRACTION...23
    CHAPTER 4...24
    PROPOSED FOREGROUND OBJECTS SEGMENTATION SYSTEMS...24
    4.1OVERVIEW OF PROPOSED SYSTEMS...25
    4.2VIDEO SEGMENTATION ARCHITECTURE...25
    4.2.1 Temporal Difference...27
    4.2.2 Multi-model Match...27
    4.2.3 Static and Dynamic Background Update...27
    4.2.4 Background Model Estimation and Foreground Extraction...32
    4.2NOISE REDUCTION ARCHITECTURE...34
    4.3.1 Shift Array Registers...37
    4.3.2 Dilation and Erosion Filter...38
    4.3OBJECT LABELING ARCHITECTURE...40
    4.4.1 Shift Array Registers...45
    4.4.2 Label Assignment...47
    4.4.3 Set Flag Registers...52
    4.4.4 Combination compare...56
    CHAPTER 5...60
    IMPLEMENTATIONS AND RESULTS...60
    5.1PROPOSED MULTI-MODEL BACKGROUND MAINTENANCE ALGORITHM QUANTITATIVE EVALUATION AND COMPARISON RESULT...61
    5.2OVERALL FOREGROUND OBJECTS SEGMENTATION SYSTEMS RESULT...63
    CHAPTER 6...71
    CONCLUSION...71
    REFERENCE...74
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    Advisor
  • Tsung-Han Tsai(½²©vº~)
  • Files
  • 965201035.pdf
  • approve in 2 years
    Date of Submission 2009-07-20

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