Measurements of External Quality of Wax Apple Using Image Processing
碩士 === 國立中興大學 === 生物產業機電工程學系 === 93 === Developing a set of on-line acquiring the external image for fruits was the purpose of this study. The wax-apple from Pingtung was applied in the experiment. Two color analog conveyer were used to acquire the top view and the side view. There are 8 parameters...
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ndltd-TW-093NCHU04150212015-10-13T15:29:19Z http://ndltd.ncl.edu.tw/handle/32565958859357627611 Measurements of External Quality of Wax Apple Using Image Processing 應用影像處理於蓮霧外部品質檢測之應用研究 Chen, JyhJye 陳志杰 碩士 國立中興大學 生物產業機電工程學系 93 Developing a set of on-line acquiring the external image for fruits was the purpose of this study. The wax-apple from Pingtung was applied in the experiment. Two color analog conveyer were used to acquire the top view and the side view. There are 8 parameters ( red area of top view, height, width, cone volume, color coordination, red, green, blue average gray of top view ) which were conducted to be analyzed from the acquired image, 6 parameters undependent were selected to be the input parameters of grading Back Propagation network model. Results of training and predicting test were shown as following: The classification rates could be reached 100% for training set and 98% for predicting set by applying the designed grading neural network model with two hidden layers and 6 neurons. XIE, GUANG-WEN 謝廣文 2005 學位論文 ; thesis 105 zh-TW |
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碩士 === 國立中興大學 === 生物產業機電工程學系 === 93 === Developing a set of on-line acquiring the external image for fruits was the purpose of this study. The wax-apple from Pingtung was applied in the experiment. Two color analog conveyer were used to acquire the top view and the side view. There are 8 parameters ( red area of top view, height, width, cone volume, color coordination, red, green, blue average gray of top view ) which were conducted to be analyzed from the acquired image, 6 parameters undependent were selected to be the input parameters of grading Back Propagation network model. Results of training and predicting test were shown as following: The classification rates could be reached 100% for training set and 98% for predicting set by applying the designed grading neural network model with two hidden layers and 6 neurons.
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XIE, GUANG-WEN |
author_facet |
XIE, GUANG-WEN Chen, JyhJye 陳志杰 |
author |
Chen, JyhJye 陳志杰 |
spellingShingle |
Chen, JyhJye 陳志杰 Measurements of External Quality of Wax Apple Using Image Processing |
author_sort |
Chen, JyhJye |
title |
Measurements of External Quality of Wax Apple Using Image Processing |
title_short |
Measurements of External Quality of Wax Apple Using Image Processing |
title_full |
Measurements of External Quality of Wax Apple Using Image Processing |
title_fullStr |
Measurements of External Quality of Wax Apple Using Image Processing |
title_full_unstemmed |
Measurements of External Quality of Wax Apple Using Image Processing |
title_sort |
measurements of external quality of wax apple using image processing |
publishDate |
2005 |
url |
http://ndltd.ncl.edu.tw/handle/32565958859357627611 |
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