Skin Texture Recognition Using Neural Networks

TL;DR

This paper presents a neural network-based skin texture recognition system that combines color and texture features, specifically GLCM-derived features, to improve accuracy in skin detection tasks.

Contribution

It introduces a novel approach that integrates texture features with color information for skin recognition using neural networks, enhancing detection performance.

Findings

High recognition accuracy achieved

Effective use of GLCM texture features

Neural network generalization demonstrated

Abstract

Skin recognition is used in many applications ranging from algorithms for face detection, hand gesture analysis, and to objectionable image filtering. In this work a skin recognition system was developed and tested. While many skin segmentation algorithms relay on skin color, our work relies on both skin color and texture features (features derives from the GLCM) to give a better and more efficient recognition accuracy of skin textures. We used feed forward neural networks to classify input textures images to be skin or non skin textures. The system gave very encouraging results during the neural network generalization face.