CLASSIFICATION OF SQUIDS USING MORPHOMETRIC MEASUREMENTS

Abstract

Rising interest in conservation and biodiversity increased the demand for accurate and consistent identification of biological objects, such as species. Among the identification issues, squids identification at the species level has been strongly addressed. Squid, is a carnivorous marine cephalopod mollusk. Each species of the squids has got its own characteristic patterns and to accurately classify the squids. In this paper we used to extract the morphometric features of the squids using image processing techniques. Here, the process begin with removing the noise of images, and then crop the images by using Region of Interest (ROI) for specified features. After then applying edge detection methods can be employed to characterize edges to represent the image for further implementation and then measure the morphometric features to estimate the type of squid based on external features like squid mantle, fin and head. Finally, For classification of squids the Artificial Neural Network (ANN) has used to classify the species based on extracted morphometric features.

Keywords

• Squids
• Region of Interest
• Edge detection
• Morphometric features
• ANN

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