An Innovative Skin Detection Approach Using Color Based Image Retrieval Technique

TL;DR

This paper introduces a novel skin detection method using color-based image retrieval that achieves high accuracy, is robust to illumination changes, and considers pixel neighborhood relations for improved detection.

Contribution

The paper presents a new skin detection approach combining CBIR with image tiling and neighborhood analysis, enhancing accuracy and robustness over existing methods.

Findings

High accuracy in skin detection across different skin types.

Robustness to illumination variations and face orientation.

Effective use of CBIR and image tiling for feature extraction.

Abstract

From The late 90th, "Skin Detection" becomes one of the major problems in image processing. If "Skin Detection" will be done in high accuracy, it can be used in many cases as face recognition, Human Tracking and etc. Until now so many methods were presented for solving this problem. In most of these methods, color space was used to extract feature vector for classifying pixels, but the most of them have not good accuracy in detecting types of skin. The proposed approach in this paper is based on "Color based image retrieval" (CBIR) technique. In this method, first by means of CBIR method and image tiling and considering the relation between pixel and its neighbors, a feature vector would be defined and then with using a training step, detecting the skin in the test stage. The result shows that the presenting approach, in addition to its high accuracy in detecting type of skin, has no sensitivity to illumination intensity and moving face orientation.