A Neural Network Based Approach For Recognition And Classification Of Color Features For Vegetables

The idea in this work is combining the GLOH algorithm and PCA to detect and classify the color features of vegetables (or) fruits. The detection and classification of color features of vegetables (or) fruits is an identified phase of research in agriculture. In technical way, image processing defines the processing of signals, gets input as an image, photo or video frame; and the output of this process can be an image or image related parameters. The aim of the paper is detecting and classifying the vegetables / fruits according to its color. It contains three parts, first two parts uses algorithms such as GLOH and SIFT-PCA, used for feature extraction and its reduction and key point extraction and dimensionality reduction. The third part of this work uses PCA to classifies the vegetables. The final result of the work is achieved by integrating the above three parts.