An Amalgam Approach for Feature Extraction and Classification of Leaves Using Support Vector Machine
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.
KeywordsFeature Extraction Classification Plant recognition Geometric Color Texture features SVM
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