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研究生:黃明益
研究生(外文):Ming-I Huang
論文名稱:基於FPGA的卡爾曼濾波器應用於膚色追蹤
論文名稱(外文):FPGA-Based Kalman Filter Application to Skin Color Tracking
指導教授:王冠智王冠智引用關係
指導教授(外文):Luke K. Wang
學位類別:碩士
校院名稱:國立高雄應用科技大學
系所名稱:電機工程系
學門:工程學門
學類:電資工程學類
論文種類:學術論文
論文出版年:101
畢業學年度:100
語文別:英文
論文頁數:69
中文關鍵詞:FPGASOPC膚色偵測邊緣檢測卡爾曼濾波器
外文關鍵詞:FPGASOPCSkin color detectionEdge detectionKalman filter
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近年來人臉偵測的應用其越來越廣泛,例如人臉身份辨識、視訊會議、數位監控系統等。在人臉偵測的前處理上,膚色是一個重要的特徵。
我們使用FPGA (Field Programmable Gate Array)發展板應用於膚色偵測追蹤系統。本論文提出了一個使用RGB顏色特徵結合Sobel邊緣檢測來找出膚色,在使用卡爾曼濾波器來估測膚色的位置,使動態攝影機可以持續的追蹤目標,使用動態攝影機追蹤目標的目的在於可以利用動態攝影機增加視角,此外利用卡爾曼濾波器來解決曝光所造成VGA的延遲也可以提高膚色偵測的辨識率。
我們使用Verilog硬體描述語言來設計膚色偵測系統來達到即時偵測的目的,此外我們利用SOPC (System on a Programmable Chip) 來創造NiosII的CPU然後藉由Avalon bus來傳輸資料,而NiosII的專案是使用C語言來撰寫。我們利用膚色偵測系統來取得膚色的座標,然後將其膚色座標藉由Avalon bus傳送到NiosII給卡爾曼濾波器來進行膚色位置的估測。
最後我們在室內的環境藉由改變不同顏色特徵的參數和使用不同的邊緣偵測來比較辨識率。
In recent years, face detection has been achieved in a wide range of applications such as human face recognition, video conference, surveillance systems, and so on. Skin color is an important feature in preprocessing of face detection.
In our investigation, we use FPGA (Field Programmable Gate Array) development board to apply skin color detection tracking system. In the thesis, we propose a method of color feature of RGB with Sobel edge detection to find skin color. We use Kalman filter algorithm to predict the position of skin color, such that active camera can keep tracking the target. The active camera is used to track the moving target for the purpose of increasing the field of view. In addition, Kalman filter can solve VGA (Video Graphics Array) delay of exposure causing and improve detection rate.
We design the skin color detection system in real time using Verilog Hardware Description Language (Verilog HDL) to achieve our aim. Furthermore, we utilize SOPC (System on a Programmable Chip) builder to create Nios II processor that is coded in C language for data transmission by Avalon bus. We capture the coordinate of skin color by skin color detection system, and then the coordinate of skin color is transferred to Nios II processor using Kalman filter to predict the position of skin color.
Finally, we change the parameters of different color feature and different edge filter to compare with detection rate in indoor environment.
CONTENTS
ABSTRACT i
摘要 iii
誌謝 iv
CONTENTS v
LIST OF FIGURES vii
LIST OF TABLES x
CHAPTER 1 INTRODUCTION 1
1.1 FPGA Embedded System 1
1.2 Face Detection 2
1.2.1 Knowledge-based Methods 3
1.2.2 Feature Invariant Approaches 3
1.2.3 Template Matching Methods 3
1.2.4 Appearance-based Methods 4
1.3 Target Tracking 4
1.4 Overview 5
CHAPTER 2 HARDWARE ARCHITECTURE 7
2.1 Altera DE2-70 Board 7
2.2 Quartus II Software 9
2.3 Nios II 11
2.4 SOPC Builder 12
2.5 TRDB-D5M 14
2.5.1 Color Filter Array 15
2.5.2 Pixel Array Structure 16
2.5.3 Binning Mode 17
2.6 VGA Display 18
2.7 Step Motor 20
CHAPTER 3 METHODOLOGY 23
3.1 Color Space 23
3.1.1 RGB Color Space 23
3.1.2 HSV Color Space 24
3.2 Edge Detection 25
3.2.1 Sobel Edge Detection 25
3.2.2 Laplacian Edge Detection 26
3.2.3 Kirsch Edge Detection 26
3.3 Kalman Filter 27
3.4 Euclidean Distance 30
CHAPTER 4 SKIN COLOR DETECTION TRACKING SYSTEM 31
4.1 Skin Color Detection 31
4.2 Tracking System 36
CHAPTER 5 EXPERIMENTAL RESULTS 43
CHAPTER 6 CONCLUSION 53
REFERENCES 54
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Lixin Chin, “FPGA Based Embedded Vision Systems,” Master Thesis, University of Western Australia, 2006.
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P. Sebastian, Y. V. Voon and R. Comley, “Colour Space Effect on Tracking in Video Surveillance,” International Journal on Electrical Engineering and Informatics, vol. 2, 2010.
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A. Tsukamoto, C. W. Lee and S. Tsuji, “Detection and Pose Estimation of Human Face with Synthesized Image Models,” International Conference on Pattern Recognition, pp. 754-757, 1994.
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“TRDB-D5M Hardware Specification,” Terasic Corporation, 2009.
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“TRDB_D5M 5 Mega Pixel Digital Camera Development Kit,” Terasic Corporation, 2010.
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G. Welch and G. Bishop, “An Introduction to the Kalman Filter,” Technical Report, University of North Carolina, 2006.
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