[1]CHEN Xiaomeng,WANG Yu,XIAO Hongbing.Identification of green plant species based on varied local edge patterns[J].CAAI Transactions on Intelligent Systems,2018,13(4):571-576.[doi:10.11992/tis.201709024]
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Identification of green plant species based on varied local edge patterns

CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume: 13 Number of periods: 2018 4 Page number: 571-576 Column: 学术论文—机器感知与模式识别 Public date: 2018-07-05
Title:
Identification of green plant species based on varied local edge patterns
Author(s):
CHEN Xiaomeng;  WANG Yu;  XIAO Hongbing
School of Computer and Information Engineering, Beijing Technology and Business University, Beijing 100048, China
Keywords:
varied local edge patterns; extraction of edge feature; identification of plant species
CLC:
TP317.41
DOI:
10.11992/tis.201709024
Abstract:
The identification of green plant species has the potential for important applications and economic value in many respects, such as protection of the environmental ecology and preparation of traditional Chinese medicine, as well as agricultural and horticultural applications. The edge of an object is an intuitive, simple, and effective object recognition feature. To overcome the shortcomings of traditional edge operators, such as few directions, single scale, and inflexible operation, in this paper, we propose a green-plant-species recognition algorithm based on circular local edge patterns, which has multiple scales and multiple directional features. We conducted a series of experiments to consider threshold subdivisions in the self-built green-plant-species database. The results show that the proposed algorithm effectively complements the edge information that is lost by the fewer edge directions and single scale of traditional edge operators, and can be effectively applied to identify green plant species.
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