A Comparative Study of Different Segmentation Algorithms on Local Fruit Images

Abstract

This project is on “A Comparative Study of Different Segmentation Algorithms on Local Fruit Images”. This paper represents the different types of segmentation algorithms on various local fruit images. In our whole work we will do various types of segmentation and the segmentation proceed on different types of local fruits shape, the lights flickered and changes color of different local fruits and the noticeable changes when the images will be segmented. The whole system contains four gradations: captured image, preliminary processing, segmentation, and Performance matrix calculation. In captured series we captured various types of local fruits with the device like as camera, in preliminary processing we diminish the noise and after that filter the noisy image to get appropriate image, in segmentation series we will work on four different types of procedure such as K-means clustering algorithms classification, Histogram base segmentation, Otsu method and Thresholding. This all segmentations are our prime need to make this paper. Arrangement of tests were carried out utilizing the proposed demonstrate on a dataset of 5 natural local fruits. Comes about of carrying out these tests illustrate that the proposed approach is competent of consequently recognize the natural product title with a tall degree of exactness.