Authors: Seok-Woo Jang; Kee-Hong Park; Gye-Young Kim
Addresses: Department of Digital Media Engineering, Anyang University, Anyang 5-Dong, Manan-Gu, Anyang 430-714, South Korea ' Department of Computer Information Engineering, National Kunsan University, 558, Daehak-Ro, Kunsan 573-701, South Korea ' Soongsil University, School of Computing, Sangdo 1-Dong, Dongjak-Gu, Seoul 156-743, South Korea
Abstract: This paper presents a new skin region extraction method that generates an image-adapted skin colour model and then segments skin areas using the model. Our method first detects eyes by using an eye map and then develops an image-adapted skin colour distribution model based on a skin map generated by reliably selecting true skin samples near the detected eyes. All skin areas over the entire image are then segmented with the generated skin model. While most of the existing skin detection methods use some pre-defined colour model, our skin model is adaptively constructed from each test image online so that it can overcome fundamental difficulties in extracting skin areas. Experimental results show that our skin extraction method gives better results as compared to other existing approaches.
Keywords: skin extraction; YCbCr space; skin colour distribution; modelling; eye map; binarisation; skin segmentation; skin detection; image segmentation.
International Journal of Computer Applications in Technology, 2015 Vol.52 No.2/3, pp.142 - 149
Received: 08 May 2021
Accepted: 12 May 2021
Published online: 26 Sep 2015 *