A Neural Network Based Recognition and Classification of Commonly Used Indian Non Leafy Vegetables
Автор: Ajit Danti, Manohar Madgi, Basavaraj S. Anami
Журнал: International Journal of Image, Graphics and Signal Processing(IJIGSP) @ijigsp
Статья в выпуске: 10 vol.6, 2014 года.
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A methodology to characterize the commonly used Indian non-leafy vegetables’ images is developed. From the captured images of Indian non-leafy vegetables, color components, namely, RGB and HSV features are extracted, analyzed and classified. A feed forward backpropagation artificial neural network (BPNN) is used for the classification. The results show that it has good robustness and a very high success rate in the range of 96-100% for eight types of vegetables. The work finds usefulness in developing recognition system for super market, automatic vending, packing and grading of vegetables, food preparation and Agriculture Produce Market Committee (APMC).
Machine vision, Digital image processing, Neural Networks classifier, Color features, Vegetable Recognition, Agricultural/horticultural produce
Короткий адрес: https://sciup.org/15013441
IDR: 15013441
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