Defect Detection in Fruits and Vegetables using K Means Segmentation and Otsu’s Thresholding

There is an escalate interest for the great quality food because of the expanding populace. In rural industry, the recognition of imperfections in fruits and vegetables is an imperative assignment, concerning the extraordinary interest for fruits and vegetables on the lookout. The customary manual assessment of fruits and vegetables grown from the ground is tedious process and it requires more human force. There might be some human mistakes. To reduce the human blunders and to accelerate the process a few philosophies for automation is presented. The various blemishes in the fruit’s and vegetable’s skin is more useful to investigate the imperfections in them.In this project, the defects in fruits and vegetables are detected through software simulation using some of the image processing techniques like K means clustering algorithm and Otsu’s thresholding method on the fruits and vegetable images, using MATLAB software. K-means clustering technique is an iterative process used to divide an image into k clusters. Pixels are clustered based on color intensity values and the images are generated to identify the defected part. The Otsu’s method is a global thresholding technique which uses the histogram of the image for threshold searching process. Simply we can say that this algorithm returns a single intensity threshold value which separates the pixels in the image into two classes, as foreground and background.