Agricultural products typically exhibit high variance in quality characteristics. To assure customer satisfaction and control manufacturing productivity, quality classification is necessary to screen off defective items and to grade the products. This article presents an application of image processing techniques on squid grading and defect discrimination. A preliminary study indicated that surface color was an efficient determinant to justify quality of splendid squids. In this study, a computer vision system (CVS) was developed to examine the characteristics of splendid squids. Using image processing techniques, squids could be classified into three different quality grades as in accordance with an industry standard. The developed system first sifted through squid images to reject ones with black marks. Qualified squids were graded on a proportion of white, pink, and red regions appearing on their bodies by using fuzzy logic. The system was evaluated on 100 images of squids at different quality levels. It was found that accuracy obtained by the proposed technique was 95% compared with sensory evaluation of an expert.