Shift and Rotation Invariant Optoelectronic Pattern Recognition Based on HSL Color Model with Liquid Crystal Correlation Filter
碩士 === 元智大學 === 光電工程學系 === 102 === This research uses the minimum average correlation energy method and shifted training images to recognize the polychromatic images based on Mach-Zehnder joint transform correlator. It leads to that the correlation output peak is much sharper and the input is proper...
Main Authors: | , |
---|---|
Other Authors: | |
Format: | Others |
Language: | zh-TW |
Online Access: | http://ndltd.ncl.edu.tw/handle/2yqqnn |
id |
ndltd-TW-102YZU05614017 |
---|---|
record_format |
oai_dc |
spelling |
ndltd-TW-102YZU056140172019-05-15T21:23:56Z http://ndltd.ncl.edu.tw/handle/2yqqnn Shift and Rotation Invariant Optoelectronic Pattern Recognition Based on HSL Color Model with Liquid Crystal Correlation Filter 液晶光電系統於HSL彩色空間之位移圖像辨識系統 Hsin-I Chen 陳心怡 碩士 元智大學 光電工程學系 102 This research uses the minimum average correlation energy method and shifted training images to recognize the polychromatic images based on Mach-Zehnder joint transform correlator. It leads to that the correlation output peak is much sharper and the input is proper to the liquid crystal device of input plane. In our former research, the training images are displayed at the center position. However, the total sidelobe energy may not be the minimum. In order to solve the problem, we transform the color image into three HSL color space components. Then, three components are rotated from 0° to 360° in steps of 5° and shifted from -5 to 5 pixels in both of vertical and the horizontal directions to yield training images. The system can deal with rotated images. Chulung Chen 陳祖龍 學位論文 ; thesis 53 zh-TW |
collection |
NDLTD |
language |
zh-TW |
format |
Others
|
sources |
NDLTD |
description |
碩士 === 元智大學 === 光電工程學系 === 102 === This research uses the minimum average correlation energy method and shifted training images to recognize the polychromatic images based on Mach-Zehnder joint transform correlator. It leads to that the correlation output peak is much sharper and the input is proper to the liquid crystal device of input plane. In our former research, the training images are displayed at the center position. However, the total sidelobe energy may not be the minimum. In order to solve the problem, we transform the color image into three HSL color space components. Then, three components are rotated from 0° to 360° in steps of 5° and shifted from -5 to 5 pixels in both of vertical and the horizontal directions to yield training images. The system can deal with rotated images.
|
author2 |
Chulung Chen |
author_facet |
Chulung Chen Hsin-I Chen 陳心怡 |
author |
Hsin-I Chen 陳心怡 |
spellingShingle |
Hsin-I Chen 陳心怡 Shift and Rotation Invariant Optoelectronic Pattern Recognition Based on HSL Color Model with Liquid Crystal Correlation Filter |
author_sort |
Hsin-I Chen |
title |
Shift and Rotation Invariant Optoelectronic Pattern Recognition Based on HSL Color Model with Liquid Crystal Correlation Filter |
title_short |
Shift and Rotation Invariant Optoelectronic Pattern Recognition Based on HSL Color Model with Liquid Crystal Correlation Filter |
title_full |
Shift and Rotation Invariant Optoelectronic Pattern Recognition Based on HSL Color Model with Liquid Crystal Correlation Filter |
title_fullStr |
Shift and Rotation Invariant Optoelectronic Pattern Recognition Based on HSL Color Model with Liquid Crystal Correlation Filter |
title_full_unstemmed |
Shift and Rotation Invariant Optoelectronic Pattern Recognition Based on HSL Color Model with Liquid Crystal Correlation Filter |
title_sort |
shift and rotation invariant optoelectronic pattern recognition based on hsl color model with liquid crystal correlation filter |
url |
http://ndltd.ncl.edu.tw/handle/2yqqnn |
work_keys_str_mv |
AT hsinichen shiftandrotationinvariantoptoelectronicpatternrecognitionbasedonhslcolormodelwithliquidcrystalcorrelationfilter AT chénxīnyí shiftandrotationinvariantoptoelectronicpatternrecognitionbasedonhslcolormodelwithliquidcrystalcorrelationfilter AT hsinichen yèjīngguāngdiànxìtǒngyúhslcǎisèkōngjiānzhīwèiyítúxiàngbiànshíxìtǒng AT chénxīnyí yèjīngguāngdiànxìtǒngyúhslcǎisèkōngjiānzhīwèiyítúxiàngbiànshíxìtǒng |
_version_ |
1719114471226474496 |