JIPS (한국정보처리학회)
Current Result Document :
| 한글제목(Korean Title) |
Multi-granular Angle Description for Plant Leaf Classification and Retrieval Based on Quotient Space |
| 영문제목(English Title) |
Multi-granular Angle Description for Plant Leaf Classification and Retrieval Based on Quotient Space |
| 저자(Author) |
Guoqing Xu
Ran Wu
Qi Wang
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| 원문수록처(Citation) |
VOL 16 NO. 03 PP. 0663 ~ 0676 (2020. 06) |
한글내용
(Korean Abstract) |
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영문내용
(English Abstract) |
Plant leaf classification is a significant application of image processing techniques in modern agriculture. In this paper, a multi-granular angle description method is proposed for plant leaf classification and retrieval. The proposed method can describe leaf information from coarse to fine using multi-granular angle features. In the proposed method, each leaf contour is partitioned first with equal arc length under different granularities. And then three kinds of angle features are derived under each granular partition of leaf contour: angle value, angle histogram, and angular ternary pattern. These multi-granular angle features can capture both local and globe information of the leaf contour, and make a comprehensive description. In leaf matching stage, the simple city block metric is used to compute the dissimilarity of each pair of leaf under different granularities. And the matching scores at different granularities are fused based on quotient space theory to obtain the final leaf similarity measurement. Plant leaf classification and retrieval experiments are conducted on two challenging leaf image databases: Swedish leaf database and Flavia leaf database. The experimental results and the comparison with state-of-the-art methods indicate that proposed method has promising classification and retrieval performance.
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| 키워드(Keyword) |
Angle Description
Image Retrieval
Leaf Classification
Multi-Granular
Quotient Space
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| 파일첨부 |
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