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논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 저널정보
- 한국정보처리학회 JIPS(Journal of Information Processing Systems) JIPS(Journal of Information Processing Systems) 제16권 제3호
- 발행연도
- 2020.1
- 수록면
- 663 - 676 (14page)
이용수
초록· 키워드
오류제보하기
Plant leaf classification is a significant application of image processing techniques in modern agriculture. Inthis paper, a multi-granular angle description method is proposed for plant leaf classification and retrieval. Theproposed method can describe leaf information from coarse to fine using multi-granular angle features. In theproposed method, each leaf contour is partitioned first with equal arc length under different granularities. Andthen three kinds of angle features are derived under each granular partition of leaf contour: angle value, anglehistogram, and angular ternary pattern. These multi-granular angle features can capture both local and globeinformation of the leaf contour, and make a comprehensive description. In leaf matching stage, the simple cityblock metric is used to compute the dissimilarity of each pair of leaf under different granularities. And thematching scores at different granularities are fused based on quotient space theory to obtain the final leafsimilarity measurement. Plant leaf classification and retrieval experiments are conducted on two challengingleaf image databases: Swedish leaf database and Flavia leaf database. The experimental results and thecomparison with state-of-the-art methods indicate that proposed method has promising classification andretrieval performance.
목차
등록된 정보가 없습니다.
참고문헌 (23)
참고문헌 신청
J. Chaki / 2015 / Plant leaf recognition using texture and shape features with neural classifiers / Pattern Recognition Letters 58:61~68
N. Liu / 2016 / Improved deep belief networks and multi-feature fusion for leaf identification / Neurocomputing 216:460~467
T. T. N. Nguyen / 2018 / Crowdsourcing for botanical data collection towards to automatic plant identification : a review / Computers and Electronics in Agriculture 155:412~425
J. Hu / 2018 / A multiscale fusion convolutional neural network for plant leaf recognition / IEEE Signal Processing Letters 25(6):853~857
J. Cao / 2016 / Similarity based leaf image retrieval using multiscale R-angle description / Information Sciences 374:51~64
N. Liu / 2016 / Improved deep belief networks and multi-feature fusion for leaf identification / Neurocomputing 216:460~467
T. T. N. Nguyen / 2018 / Crowdsourcing for botanical data collection towards to automatic plant identification : a review / Computers and Electronics in Agriculture 155:412~425
J. Hu / 2018 / A multiscale fusion convolutional neural network for plant leaf recognition / IEEE Signal Processing Letters 25(6):853~857
J. Cao / 2016 / Similarity based leaf image retrieval using multiscale R-angle description / Information Sciences 374:51~64
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