NDLI: An algorithm of excising leafstalk while keeping its main body intact for leaf recognition

Content Provider	IEEE Xplore Digital Library
Author	Liwen Gao Xiaohua Lin Wenguang Zhao Shu Chen Huajun Huang
Copyright Year	2010
Description	Author affiliation: Coll. of Inf. Technol., Guangzhou Univ. of Chinese, Med., Guangzhou, China (Liwen Gao; Wenguang Zhao; Shu Chen; Huajun Huang) \|\| Coll. of Chinese Materia Medica, Guangzhou Univ. of Chinese, Med., Guangzhou, China (Xiaohua Lin)
Abstract	The machine recognition of leaf images is a fast and effective plant classification method. However, the existence of redundant leafstalks affects the recognition accuracy seriously and hinders the recognition of leaves on branches. Currently, most research avoid this problem and only Wang et al. proposed applying the opening operation to erase leafstalks. But as the experimental analyses show, the method is infeasible because it is difficult to determine the size of the structure element. Herein, we propose a new algorithm of excising leafstalk. Through the experimental verification, it can complete the accurate excision of the redundant leafstalk while keeping its main body intact.
Sponsorship	IEEE
Starting Page	2732
Ending Page	2736
File Size	647695
Page Count	5
File Format	PDF
ISBN	9781424465132
e-ISBN	9781424465163
DOI	10.1109/CISP.2010.5647617
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-10-16
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	leafstalk excision Accuracy Image recognition Signal processing algorithms Artificial neural networks Feature extraction leaf recognition opening operation Classification algorithms Biomedical imaging
Content Type	Text
Resource Type	Article

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