Title :
Hand image segmentation under selective illuminations
Author :
Sui, Chao ; Kwok, Ngai Ming ; Ren, Tianran
Author_Institution :
Sch. of Mech. & Manuf. Eng., Univ. of New South Wales, Sydney, NSW, Australia
Abstract :
A hand image segmentation method with focuses in constructing Gaussians mixture models (GMMs) for hand skin color is proposed. The Expectation Maximization (EM) algorithm is used for estimating parameters for GMM, and the Receiver Operating Characteristic (ROC) curve is employed for determining a threshold. Experimental results show that two thresholds, which are an overall probability threshold and a hue value threshold, are more capable of achieving ideal segmenting results than a single threshold.
Keywords :
Gaussian processes; expectation-maximisation algorithm; image colour analysis; image segmentation; Gaussians mixture models; expectation maximization algorithm; hand image segmentation; hand skin color; hue value threshold; probability threshold; receiver operating characteristic curve; selective illuminations; Computational modeling; Conferences; Image color analysis; Image segmentation; Lighting; Mathematical model; Skin;
Conference_Titel :
Image and Signal Processing (CISP), 2010 3rd International Congress on
Conference_Location :
Yantai
Print_ISBN :
978-1-4244-6513-2
DOI :
10.1109/CISP.2010.5648268
