Pattern Recognition by the Multi-Channel Liquid Crystal Optoelectronic Correlator with Shifted Training Images

碩士 === 元智大學 === 光電工程學系 === 100 === In this research, using Minimum average correlation energy (MACE) method and shifted to recognize the polychromatic images. In our past research, training images are disposed the center. However, the total sidelobe energy may not be the minimum. In order to improve...

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Main Authors: Cheng-Hsuan Yu, 游承軒
Other Authors: 陳祖龍
Format: Others
Language:zh-TW
Online Access:http://ndltd.ncl.edu.tw/handle/08664831866596904654
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spelling ndltd-TW-100YZU056141522015-10-13T21:33:10Z http://ndltd.ncl.edu.tw/handle/08664831866596904654 Pattern Recognition by the Multi-Channel Liquid Crystal Optoelectronic Correlator with Shifted Training Images 多通道液晶光電相關器於位移圖像辨識 Cheng-Hsuan Yu 游承軒 碩士 元智大學 光電工程學系 100 In this research, using Minimum average correlation energy (MACE) method and shifted to recognize the polychromatic images. In our past research, training images are disposed the center. However, the total sidelobe energy may not be the minimum. In order to improve it, we decomposed the polychromatic images into 3 R, G and B components, and then rotated from 0° to 360° in steps of 5°, shifted from -5 pixel to 5 pixel in both the vertical direction and the horizontal direction to generate many training images. Finally, by using the MACE method and cross correlation operation, the filter with minimum sidelobe energy on the output plane can be obtained, so as to increase the recognition ability. 陳祖龍 學位論文 ; thesis 52 zh-TW
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language zh-TW
format Others
sources NDLTD
description 碩士 === 元智大學 === 光電工程學系 === 100 === In this research, using Minimum average correlation energy (MACE) method and shifted to recognize the polychromatic images. In our past research, training images are disposed the center. However, the total sidelobe energy may not be the minimum. In order to improve it, we decomposed the polychromatic images into 3 R, G and B components, and then rotated from 0° to 360° in steps of 5°, shifted from -5 pixel to 5 pixel in both the vertical direction and the horizontal direction to generate many training images. Finally, by using the MACE method and cross correlation operation, the filter with minimum sidelobe energy on the output plane can be obtained, so as to increase the recognition ability.
author2 陳祖龍
author_facet 陳祖龍
Cheng-Hsuan Yu
游承軒
author Cheng-Hsuan Yu
游承軒
spellingShingle Cheng-Hsuan Yu
游承軒
Pattern Recognition by the Multi-Channel Liquid Crystal Optoelectronic Correlator with Shifted Training Images
author_sort Cheng-Hsuan Yu
title Pattern Recognition by the Multi-Channel Liquid Crystal Optoelectronic Correlator with Shifted Training Images
title_short Pattern Recognition by the Multi-Channel Liquid Crystal Optoelectronic Correlator with Shifted Training Images
title_full Pattern Recognition by the Multi-Channel Liquid Crystal Optoelectronic Correlator with Shifted Training Images
title_fullStr Pattern Recognition by the Multi-Channel Liquid Crystal Optoelectronic Correlator with Shifted Training Images
title_full_unstemmed Pattern Recognition by the Multi-Channel Liquid Crystal Optoelectronic Correlator with Shifted Training Images
title_sort pattern recognition by the multi-channel liquid crystal optoelectronic correlator with shifted training images
url http://ndltd.ncl.edu.tw/handle/08664831866596904654
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