Performance Comparison of Edge Detection Method for Extracting Images of Lutjanus spp. Contour

Abstract

Lutjanus spp. is one of the 72 genera of fish species which includes to the Lutjanidae family around the world. The Lutjanus spp. is healthy for consumption and suitable for fishing tourism. The production volume increased by 6.21% between 2001 and 2011 to produce over 118608 tons. However, about 10 species are experiencing population decline. This is because the data of captured fisheries production is still limited, making it challenging to identify the species resulting in overfishing of certain species. The process of identifying the species is based on morphometric characteristics using edge detection. This method involves a pattern identification technique by detecting outlines at the boundaries of objects in the image. In this research, several edge detection algorithms were conducted following many steps to clarify contour extraction of Lutjanus spp. (L. argentimaculatus, L. bohar, L. carponatatus, L. fulviflamma, and L. sebae). The steps included image preprocessing, shape extraction with edge detection algorithms involving the Sobel, Canny, and Laplacian operations, and visual evaluation. The results showed that the three algorithms could be used to extract the contours of Lutjanus spp. The Laplacian algorithm produced the best performance because it could extract the contours with a success rate of 89.88% without noise or broken contours.