• Kayathiri M
• Krishnaveni K
• Ponmalar K

Newsday’s plant classification based on leaf identification is becoming a popular. Plants are fundamental for human beings, so it's play vital role categorize and preserve all the plants. Each leaf carries significantly information that can be used to identify and classify the origin of the plant. An image processing techniques based on leaves recognition can help to find the best features useful for plant representation and classification. In this research we propose a leaf recognition method which uses a new features set that incorporates shape, color and texture features. A total of 760 leaf features are extracted and used for training a SVM classification learner App. The method has been tested on input dataset showing excellent performance both in terms of accuracy that often reaches 96%, color features.

Leaf images, Preprocessing, Feature Extraction, shape, color and texture features, SVM Classification.

"Medicinal Plant Classification and Analysis Using SVM Classifier Kernel Functions", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 6, page no.176-183, June 2019, Available :http://www.jetir.org/papers/JETIR1906Z26.pdf

"Medicinal Plant Classification and Analysis Using SVM Classifier Kernel Functions", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 6, page no. pp176-183, June 2019, Available at : http://www.jetir.org/papers/JETIR1906Z26.pdf