Low Cost Skin Segmentation Scheme in Videos Using Two Alternative Methods for Dynamic Hand Gesture Detection Method

Abstract

Recent years have witnessed renewed interest in developing skin segmentation approaches. Skin feature segmentation has been widely employed in different aspects of computer vision applications including face detection and hand gestures recognition systems. This is mostly due to the attractive characteristics of skin colour and its effectiveness to object segmentation. On the contrary, there are certain challenges in using human skin colour as a feature to segment dynamic hand gesture, due to various illumination conditions, complicated environment, and computation time or real-time method. These challenges have led to the insufficiency of many of the skin color segmentation approaches. Therefore, to produce simple, effective, and cost efficient skin segmentation, this paper has proposed a skin segmentation scheme. This scheme includes two procedures for calculating generic threshold ranges in Cb-Cr colour space. The first procedure uses threshold values trained online from nose pixels of the face region. Meanwhile, the second procedure known as the offline training procedure uses thresholds trained out of skin samples and weighted equation. The experimental results showed that the proposed scheme achieved good performance in terms of efficiency and computation time.

The Landscape of Research on Skin Detectors: Coherent Taxonomy, Open Challenges, Motivations, Recommendations and Statistical Analysis, Future Directions

“…Majority of the research in skin detection are focusing on design and development of Skin Detection Classifiers, Techniques and Methods [34], [45], [62], [64], [66], [79], [80], [93], [95], [100], [104], [133], [144], [152], [157], [167]. Therefore there is a need to properly formulate the skin detector, overcoming all the difficulties that arise in detecting skin in an image.…”

“…A high level method of extracting hand features for the purpose of recognizing real-time gesture was presented in study [16] The process of developing a model of skin model based on ellipse clustering was presented in [143], and image was detected using the model of skin color. In the last paper, a scheme which includes two procedures for the calculation of generic threshold ranges of Cb-Cr color, was proposed for the segmentation of skin [144].…”

“…Some authors [37], [42], [52], [73], [81], [111], [134], and [164] have noted that one of the challenges is that of varying conditions of illumination that can be adapted to the detection of human skin. Researcher also found that even after implementation of certain methods, the illumination still posed challenges in skin detection methods [12], [45], [87], [144], [165]. As for example, in [45] stated ''Unlike traditional machine learning methods, instead of predicting each pixel individually, our algorithm utilizes blocks to learn the representations and detect the skin areas.…”

Multifeature Fusion Detection Method for Fake Face Attack in Identity Authentication

“…Furthermore, removing the eye part in the photo and using face photos and real human eye rotation all spoof the detection system. [3]. Video deception [3] uses cameras, pinhole cameras, and other means to shoot videos of the legitimate user, which poses a great threat to the facial recognition system.…”

“…[3]. Video deception [3] uses cameras, pinhole cameras, and other means to shoot videos of the legitimate user, which poses a great threat to the facial recognition system. Compared to the photo, the video can obtain head or facial movement and eye information from the blink of eye movement.…”