A Comparative Study to find an Effective Image Segmentation Technique using Clustering to obtain the Defective Portion of an Apple

This paper aims at quality evaluation of the apple fruit to identify the surface defects based on the application of image processing and the computer vision systems. The external appearance of a fruit is one of the most important quality features and the manual assessment of the same by the human inspectors is costly, highly variable and inconsistent. Hence to meet the ever-increasing demand for the uniform and high-quality fruits, an automated visual inspection technique using computer vision and image processing will undoubtedly be the preferred method. A crucially significant process for the automated fruit grading system is image segmentation. A comparative end result of the segmentation techniques based on the concept of clustering to find the defective portion of the apple fruit is presented. The motivation behind the proposed method is to improve the time complexity and accuracy of the clustering technique with the use of preprocessing.