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An Amalgam Approach for Feature Extraction and Classification of Leaves Using Support Vector Machine

Part of the Advances in Intelligent and Soft Computing book series (AINSC, volume 166)

Abstract

This paper describes the need for the development of automatic plant recognition system for classification of plant leaves. In this paper, an automatic Computer Aided Plant Leaf Recognition (CAP-LR) is presented. To implement the above system initially the input image is pre-processed in order to remove the background noise and to enhance the leaf image. As a second stage the system efficiently extracts the different feature vectors of the leaves and gives it as input to the Support Vector Machine (SVM) for classification into plant leaves or tree leaves. Geometric, texture and color features are extracted for classification. The method is validated by K-Map which calculates the accuracy, sensitivity and efficiency. The experimental result shows that the system has faster processing speed and higher recognition rate.

Keywords

Feature Extraction Classification Plant recognition Geometric Color Texture features SVM 

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Copyright information

© Springer-Verlag GmbH Berlin Heidelberg 2012

Authors and Affiliations

  1. 1.Department Computer ScienceAvinashilingam Institute of Home Science and Higher Education for WomenCoimbatoreIndia

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