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http://dx.doi.org/10.9717/kmms.2014.17.3.300

Plant leaf Classification Using Orientation Feature Descriptions  

Gang, Su Myung ((주)지오씨엔아이 공간정보기술연구소)
Yoon, Sang Min (국민대학교 컴퓨터공학부)
Lee, Joon Jae (계명대학교 게임모바일콘텐츠학과)
Publication Information
Journal of Korea Multimedia Society / v.17, no.3, 2014 , pp. 300-311 More about this Journal
Abstract
According to fast change of the environment, the structured study of the ecosystem by analyzing the plant leaves are needed. Expecially, the methodology that searches and classifies the leaves from captured from the smart device have received numerous concerns in the field of computer science and ecology. In this paper, we propose a plant leaf classification technique using shape descriptor by combining Scale Invarinat Feature Transform (SIFT) and Histogram of Oriented Gradient (HOG) from the image segmented from the background via Graphcut algorithm. The shape descriptor is coded in the field of Locality-constrained Linear Coding to optimize the meaningful features from a high degree of freedom. It is connected to Support Vector Machines (SVM) for efficient classification. The experimental results show that our proposed approach is very efficient to classify the leaves which have similar color, and shape.
Keywords
Plant Recognition; LLC; Feature Extraction;
Citations & Related Records
Times Cited By KSCI : 4  (Citation Analysis)
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