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研究生:丁志傑
研究生(外文):Chih-Chieh Ting
論文名稱:液晶空間光調制器於光電相關系統做彩色影像識別的研究
論文名稱(外文):Color image recognition based on optoelectronic correlator with liquid-crystal spatial light modulator
指導教授:陳祖龍
指導教授(外文):Chulung Chen
學位類別:碩士
校院名稱:元智大學
系所名稱:電機工程學系
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:2004
畢業學年度:92
語文別:英文
論文頁數:54
中文關鍵詞:聯合轉換相關器影像編碼最小平均相關能量
外文關鍵詞:joint transform correlatorimage encodingminimum average correlation energy
相關次數:
  • 被引用被引用:0
  • 點閱點閱:136
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  • 下載下載:0
  • 收藏至我的研究室書目清單書目收藏:1
本論文中我們提出了一個新的方法,應用在聯合轉換相關器的彩色影像識別系統。此技術是利用影像編碼將每一個彩色目標影像轉換到灰階影像。當輸入為灰階或單色時,就可利用液晶光調制器來達到及時性的運作。在另一方面,我們使用最小平均相關能量的方法,去設計一個最佳化的合成參考函數。除此之外,我們也利用功率頻譜相減的方法,來移除輸出面上的零階項,使預期的相關峰值看得較明顯。
為了證實我們所提出的方法是有成效的。最後,我們藉由電腦的數值計算來測試評估雜訊及形變的目標影像,如PCE、PSR、及CPIR等。此時我們發現新的聯合轉換相關器擁有較高的影像辨識力和偵測能力。

In this thesis, we propose a novel method for color pattern recognition based on the joint transform correlator architecture. In the method each color target image is transformed to a grayscale image with image encoding technique. The input plane is gray-scaled and monochromatic, thus it can be displayed in the liquid-crystal spatial light modulator to achieve real-time operation. On the other hand, we use minimum average correlation energy approach to design an optimized synthetic reference function. Moreover, we adopt the joint transform power spectrum subtraction strategy to remove zero order part at the output plane, and the desired correlation peaks can be easily detected.
At the end, we study system’s performance for noise and distorted images numerically. Thus, we show that the novel joint transform correlator has higher pattern discrimination ability and detection ability.

Chinese Abstract i
English Abstract ii
Acknowledgement iii
Contents iv
Figure Captions vi
Tables viii
Chapter 1 Introduction 1
Chapter 2 Theoretical Analysis 4
2.1. Conventional joint transform correlator system 4
2.2. Non-zero order JTC system 6
2.3. Analysis 8
2.4. Image encoding method 14
2.5. MACE method 16
2.6 . Performance criteria 20
2.6.1. Correlation peak intensity ratio (CPIR) 20
2.6.2. Peak to correlation energy (PCE) 21
2.6.3. Peak to sidelobe ratio (PSR) 21
2.6.4. Input signal to noise ratio (SNR) 22
Chapter 3 Numerical Results 23
3.1. Result for a noise-free input image 26
3.1.1. Monochromatic NOJTC 26
3.1.2. Polychromatic NOJTC with encoding technique 28
3.2. Results for target images both in and not in the training set 31
3.3. Results for noisy images 37
3.4. Results for input image with non-target object 41
3.5. Results for input image with background 44
3.6. The influence of training images number 47
Chapter 4 Conclusions 50
References 52

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