Quality Evaluation of Apple Fruit for Automated Food Processing

Quality inspection of fruits with help of computer vision or image processing is gaining much attention nowadays because of the costly and labor intensive techniques used earlier. It has been proven much useful to the agricultural sectors and other industries in the past. The present research work is based on the quality evaluation of apple fruit. Since less work is done for the quality evaluation of internal part of apple, i.e. slices, here the experiment will be done; first on the external surface and then on the slices. Here hue histogram intersection is used for external surface defect detection and for slices defect checking; features called Color Coherence Vector and Complete Local Binary Patterns are extracted from the slice images and they are given as input to Multi-Class Support Vector Machine classifier. Both linear and nonlinear SVMs were used and linear classification gave better results.