A Neural Network Based Recognition and Classification of Commonly Used Indian Non Leafy Vegetables
Open Access
- 8 September 2014
- journal article
- Published by MECS Publisher in International Journal of Image, Graphics and Signal Processing
- Vol. 6 (10) , 62-68
Abstract
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).Keywords
This publication has 5 references indexed in Scilit:
- A Neural Network Based Recognition and Classification of Commonly Used Indian Non Leafy VegetablesInternational Journal of Image, Graphics and Signal Processing, 2014
- Automatic fruit and vegetable classification from imagesComputers and Electronics in Agriculture, 2010
- Effects of Classification Methods on Color-Based Feature Detection With Food Processing ApplicationsIEEE Transactions on Automation Science and Engineering, 2007
- Pizza sauce spread classification using colour vision and support vector machinesJournal of Food Engineering, 2005
- VeggieVision: a produce recognition system2002