An Effective Pixel-Wise Approach for Skin Colour Segmentation Using Pixel Neighbourhood Technique

TL;DR

This paper introduces a two-stage pixel neighbourhood method utilizing deep neural networks for improved skin colour segmentation that adapts to varied skin tones and lighting conditions.

Contribution

It proposes a novel pixel neighbourhood technique combining neural network probabilities with local context for more accurate skin segmentation.

Findings

Outperforms existing skin segmentation methods

Effective under diverse lighting and skin tones

Utilizes deep learning for pixel classification

Abstract

This paper presents a novel technique for skin colour segmentation that overcomes the limitations faced by existing techniques such as Colour Range Thresholding. Skin colour segmentation is affected by the varied skin colours and surrounding lighting conditions, leading to poorskin segmentation for many techniques. We propose a new two stage Pixel Neighbourhood technique that classifies any pixel as skin or non-skin based on its neighbourhood pixels. The first step calculates the probability of each pixel being skin by passing HSV values of the pixel to a Deep Neural Network model. In the next step, it calculates the likeliness of pixel being skin using these probabilities of neighbouring pixels. This technique performs skin colour segmentation better than the existing techniques.