Fish recognition based on the combination between robust feature selection, image segmentation and geometrical parameter techniques using Artificial Neural Network and Decision Tree

TL;DR

This paper introduces a novel fish classification method combining robust feature selection, image segmentation, and geometrical parameters, utilizing neural networks and decision trees to improve fish recognition accuracy.

Contribution

It proposes a comprehensive feature extraction approach with weighted features as prior information, focusing on input data selection rather than classifier structure improvements.

Findings

Effective fish categorization into clusters, poison/non-poison, and family.

Enhanced recognition accuracy using combined feature techniques.

Prototype implementation demonstrates practical applicability.

Abstract

We presents in this paper a novel fish classification methodology based on a combination between robust feature selection, image segmentation and geometrical parameter techniques using Artificial Neural Network and Decision Tree. Unlike existing works for fish classification, which propose descriptors and do not analyze their individual impacts in the whole classification task and do not make the combination between the feature selection, image segmentation and geometrical parameter, we propose a general set of features extraction using robust feature selection, image segmentation and geometrical parameter and their correspondent weights that should be used as a priori information by the classifier. In this sense, instead of studying techniques for improving the classifiers structure itself, we consider it as a black box and focus our research in the determination of which input information must bring a robust fish discrimination.The main contribution of this paper is enhancement recognize and classify fishes based on digital image and To develop and implement a novel fish recognition prototype using global feature extraction, image segmentation and geometrical parameters, it have the ability to Categorize the given fish into its cluster and Categorize the clustered fish into poison or non-poison fish, and categorizes the non-poison fish into its family .