Development of an image processing system in splendid squid grading

Abstract

Quality inspection of commercial squids is a labor intensive process. This study proposes an approach to develop a computer vision system for size and specie classification of squids. Both species were differentiated by distinction of mantle shapes. A Multi Layer Perceptron (MLP) with a back propagation algorithm was used to sort squid samples to pre-defined sizes based on a standard of National Bureau of Agricultural Commodity and Food Standards (ACFS). Features extracted from squid images including area, perimeter and length of the squid mantle were used as parameters into the network. Differences between species could be distinguished by using a ratio of length and width of the squid mantle. Results showed that approximately 90 classification accuracy could be achieved from the approach proposed in this study. © 2013 Springer-Verlag.