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The Categorization Algorithms Using Edge Detection for Plant Recognition System

As smart phones are becoming new means of gathering and sharing information, the demands for the smart phone ‘apps’ providing plant information and data are also increasing. This study is to provide the algorithms to identify plants using their leaves and is also to feature the digitized leaf data to be stored in the database to be used for plant identification applications. Outline ‘edge’ data of the leaf are extracted by using SP Sweeping algorithm, and the plant species are categorized and identified by applying six algorithms: H/W ratio, top-tip ratio, bottom-tip ratio, gradient of edge points, distance between edge point and the center, and second degree polynomial approximation algorithms. Thirty two species have been selected and used to validate the algorithms. H/W ratio and top-tip ratio have been found to be very effective algorithms to distinguish many species. Moreover, gradient and distance methods have shown the recognizable differences between species, and Bhattacharyya distances have been found to be a great data to be stored as a part of analysis data for run-time comparison by application. Additionally, this study also has confirmed the feasibility of additional identification categories using the features of petiole and tip as well as characteristics of the leaf margin.