An Automatic Recognition System of Leaves

碩士 === 國立交通大學 === 多媒體工程研究所 === 96 === When wandering around the field, we can touch many plants. It is useful knowing them through image recognition technique. Since leaf is one of the important features for characterizing various plants, it is often taken for plant recognition. The thesis proposes...

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Main Authors: Hsun-Ying Huang, 黃薰瑩
Other Authors: Ling-Hwei Chen
Format: Others
Language:en_US
Published: 2008
Online Access:http://ndltd.ncl.edu.tw/handle/73164125976634594993
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spelling ndltd-TW-096NCTU56410262015-10-13T12:18:06Z http://ndltd.ncl.edu.tw/handle/73164125976634594993 An Automatic Recognition System of Leaves 一個自動化葉片辨識系統 Hsun-Ying Huang 黃薰瑩 碩士 國立交通大學 多媒體工程研究所 96 When wandering around the field, we can touch many plants. It is useful knowing them through image recognition technique. Since leaf is one of the important features for characterizing various plants, it is often taken for plant recognition. The thesis proposes a hierarchical automatic region-based method for leaf recognition. First, delete impossible species to which the input leaf belongs according to the leaf shape represented by five extracted features. Next, based on these candidates, the system finds out the most similar images in our database and allows each user to choose the correct one. The precision rate is 95.14% for top 5. In addition, the proposed method is rotation invariant and solves the noises caused by light reflection in preprocessing. Ling-Hwei Chen 陳玲慧 2008 學位論文 ; thesis 27 en_US
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description 碩士 === 國立交通大學 === 多媒體工程研究所 === 96 === When wandering around the field, we can touch many plants. It is useful knowing them through image recognition technique. Since leaf is one of the important features for characterizing various plants, it is often taken for plant recognition. The thesis proposes a hierarchical automatic region-based method for leaf recognition. First, delete impossible species to which the input leaf belongs according to the leaf shape represented by five extracted features. Next, based on these candidates, the system finds out the most similar images in our database and allows each user to choose the correct one. The precision rate is 95.14% for top 5. In addition, the proposed method is rotation invariant and solves the noises caused by light reflection in preprocessing.
author2 Ling-Hwei Chen
author_facet Ling-Hwei Chen
Hsun-Ying Huang
黃薰瑩
author Hsun-Ying Huang
黃薰瑩
spellingShingle Hsun-Ying Huang
黃薰瑩
An Automatic Recognition System of Leaves
author_sort Hsun-Ying Huang
title An Automatic Recognition System of Leaves
title_short An Automatic Recognition System of Leaves
title_full An Automatic Recognition System of Leaves
title_fullStr An Automatic Recognition System of Leaves
title_full_unstemmed An Automatic Recognition System of Leaves
title_sort automatic recognition system of leaves
publishDate 2008
url http://ndltd.ncl.edu.tw/handle/73164125976634594993
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