Optimal training image registration for optical correlation synthesis
碩士 === 元智大學 === 電機工程學系 === 90 === Abstract In our previous published papers on the non-zero order opto-electronic joint transform correlator, classical training images are put around the center to synthesize the reference function. However, it can’t guarantee that minimum average cross co...
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ndltd-TW-090YZU004420022017-06-02T04:42:14Z http://ndltd.ncl.edu.tw/handle/76807742829048821905 Optimal training image registration for optical correlation synthesis 光學相關濾波器之最佳化影像位置的研究 Yeao-Hwang Chung 鍾耀寰 碩士 元智大學 電機工程學系 90 Abstract In our previous published papers on the non-zero order opto-electronic joint transform correlator, classical training images are put around the center to synthesize the reference function. However, it can’t guarantee that minimum average cross correlation energy can be achieved. To improve this, we shift training images pixel by pixel from the left to the right and from the top to the bottom. We record the power spectrum and calculate the reference function to find minimum average cross correlation energy while shifting the training image each time. By this procedure, the optimal training image database will be found. Compared with the original method, our method will get sharp correlation peaks and less sidelobes, which can increase the recognition efficiency and reduce false alarm rates. Chulung Chen 陳祖龍 2002 學位論文 ; thesis 56 zh-TW |
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碩士 === 元智大學 === 電機工程學系 === 90 === Abstract
In our previous published papers on the non-zero order opto-electronic joint transform correlator, classical training images are put around the center to synthesize the reference function. However, it can’t guarantee that minimum average cross correlation energy can be achieved.
To improve this, we shift training images pixel by pixel from the left to the right and from the top to the bottom. We record the power spectrum and calculate the reference function to find minimum average cross correlation energy while shifting the training image each time. By this procedure, the optimal training image database will be found. Compared with the original method, our method will get sharp correlation peaks and less sidelobes, which can increase the recognition efficiency and reduce false alarm rates.
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Chulung Chen |
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Chulung Chen Yeao-Hwang Chung 鍾耀寰 |
author |
Yeao-Hwang Chung 鍾耀寰 |
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Yeao-Hwang Chung 鍾耀寰 Optimal training image registration for optical correlation synthesis |
author_sort |
Yeao-Hwang Chung |
title |
Optimal training image registration for optical correlation synthesis |
title_short |
Optimal training image registration for optical correlation synthesis |
title_full |
Optimal training image registration for optical correlation synthesis |
title_fullStr |
Optimal training image registration for optical correlation synthesis |
title_full_unstemmed |
Optimal training image registration for optical correlation synthesis |
title_sort |
optimal training image registration for optical correlation synthesis |
publishDate |
2002 |
url |
http://ndltd.ncl.edu.tw/handle/76807742829048821905 |
work_keys_str_mv |
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