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Publication Type : Conference Paper
Publisher : 2017 International Conference on Advances in Computing, Communications and Informatics (ICACCI)
Source : 2017 International Conference on Advances in Computing, Communications and Informatics (ICACCI) (2017)
Keywords : biology computing, Biomedical imaging, botany, dataset collection, Feature extraction, Gray Level Co occurrence Matrix, Histograms, HOG, image classification, Image color analysis, Image pre processing, leaf features, Medicinal plants, medicinal values, Shape, Standards, Support vector machine algorithm, support vector machine based classification, Support vector machines, SVM
Campus : Coimbatore
School : School of Engineering
Department : Computer Science, Sciences
Verified : Yes
Year : 2017
Abstract : Nature has surrounded us with lot of plants having medicinal values. But most of the time, we don't realize the importance and benefits of the plant and we just ignore it. In other cases, though we know names of the plants with medicinal values, it becomes difficult to identify the plant even if it is naturally grown in our backyard. And hence, a system is developed which would provide a solution for this by identifying the plant and providing it's medicinal values, thereby helping in the cure of many ailments in a natural way. This paper discusses about the dataset collection, feature extraction using texture and HOG and thereby classifying based on Support Vector Machine algorithm.
Cite this Research Publication : D. Venkataraman and Mangayarkarasi, N., “Support Vector Machine based Classification of Medicinal Plants using Leaf Features”, in 2017 International Conference on Advances in Computing, Communications and Informatics (ICACCI), 2017.