Title: Identifying herbal leaves using shape context with ant colony and bipartite matching

Authors: I. Kiruba Raji; K.K. Thyagharajan

Addresses: RMD Engineering College, Chennai – 601206, India ' RMD Engineering College, Chennai – 601206, India

Abstract: Leaves are assuming basic part in today's life, on the grounds that numerous leaves are going about as herbs to plan drugs to cure diseases. In any case, every one of the leaves cannot be arranged effectively as herbs by people. To maintain a strategic distance from such trouble, we need to examine the morphological characters of every leave in light of the fact that morphological qualities of every plant and leaf differ for every crew. For breaking down morphological characters of leaves PCs are utilised, in the field of software engineering computerised picture handling strategies are utilised to investigate the pictures painstakingly. In this paper, we present shape context which is accustomed to extricating different elements from leaves, rather than separating symmetry driven components by SIFT, relative and SURF operators. Shape context is utilised to concentrate nearby and worldwide components from form focuses. In the wake of extricate components, for perceiving leaves delicate processing systems, for example, ant colony optimisation and bipartite matching calculations are utilised.

Keywords: object recognition; morphological characters; shape context; ant colony optimisation; ACO; bipartite matching; herbal leaves; leaf shapes; morphology; software engineering; picture handling; feature extraction; leaf identification.

DOI: 10.1504/IJTMCP.2016.077921

International Journal of Telemedicine and Clinical Practices, 2016 Vol.1 No.3, pp.265 - 276

Received: 24 Jun 2015
Accepted: 29 Sep 2015

Published online: 22 Jul 2016 *

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