Accurate Pixel-Wise Skin Segmentation Using Shallow Fully Convolutional Neural Network

Komal Minhas,Syed Saud Naqvi,Haroon Ahmed Khan,Tariq M Khan,Muhammad Arsalan,Mansoor Ahmed,Abdul Haseeb,Muhammad Adnan Haider

doi:10.1109/access.2020.3019183

Abstract

Skin segmentation plays an important role in human activity recognition, video surveillance, hand gesture identification, face detection, human tracking and robotic surgery. The accurate segmentation of the skin is necessary to recognize the human activity. Segmentation of skin is easy to realize in ideal situations because of similar backgrounds. But it becomes complicated because of presence of skin-like pixels, background illuminations, and certain changes in environment. These problems are addressed by incorporating preprocessing stages in current studies, but this raises the total cost of the system. However, there are some limitations associated with these methods in terms of accuracy and processing speed. In this work, we propose a skin semantic segmentation network (SSS-Net) that is able to capture the multi-scale contextual information and refines the segmentation results especially along object boundaries. Moreover our network helps to reduce the cost of the preprocessing as well. We have performed experiments on the five open datasets of human activity recognition for the segmentation of skin. Experimental results show SSS-Net outperforms the state-of-the-art methods in skin segmentation in terms of accuracies.

Highlights

S KIN segmentation aims to detect the region of a human skin in an image
We propose skin semantic segmentation network (SSS-Net) for skin segmentation that eliminates the preprocessing steps and uses a reduced number of parameters compared to existing solutions
EXPERIMENTAL DATA AND ENVIRONMENT SSS-Net was tested for skin segmentation using five datasets of human activity recognition that are publicly available [8]

Summary

Introduction

S KIN segmentation aims to detect the region of a human skin in an image. It is one of the important tasks which works as a step for pre-processing in various systems and applications , such as hand gesture analysis, face recognition, face tracking and detection, content based image retrieval, etc. Skin detection is very helpful to humans while performing complex tasks through human computer interaction. As in case of hand gesture recognition, it provides help in recognizing certain actions [2]. With the advancements in deep neural networks, the networks used for other detection tasks have been adapted as skin detection methods as well [3], [4]

Methods

Results

Discussion

Conclusion