Comparative Analysis of Various Soft Computing Techniques for Classification of Fruits

Fruit classification and recognition techniques play a significant role in various fruit based computer vision systems. Many techniques have been proposed so far to classify and recognize fruit images. However, these techniques not provide efficient results whenever fruit images have poor visibility due to poor environmental conditions. The overall objective of this paper is to study and explore various techniques which have been designed so far to classify and recognize fruit images. Comparisons have been drawn between some well-known fruit classification and recognition techniques based upon certain features. It has been observed that soft computing based fruit classification and recognition techniques performs efficiently than existing techniques.