title: An Interactive Image Segmentation Method in Hand Gesture Recognition.
abstract: In order to improve the recognition rate of hand gestures a new interactive image segmentation method for hand gesture recognition is presented, and popular methods, e.g., Graph cut, Random walker, Interactive image segmentation using geodesic star convexity, are studied in this article. The Gaussian Mixture Model was employed for image modelling and the iteration of Expectation Maximum algorithm learns the parameters of Gaussian Mixture Model. We apply a Gibbs random field to the image segmentation and minimize the Gibbs Energy using Min-cut theorem to find the optimal segmentation. The segmentation result of our method is tested on an image dataset and compared with other methods by estimating the region accuracy and boundary accuracy. Finally five kinds of hand gestures in different backgrounds are tested on our experimental platform, and the sparse representation algorithm is used, proving that the segmentation of hand gesture images helps to improve the recognition accuracy.
authors.affiliation: School of Machinery and Automation, Wuhan University of Science and Technology, Wuhan 430081, China. chendisi123@126.com.
authors.forename: Disi
authors.initials: D
authors.lastname: Chen
authors.affiliation: School of Machinery and Automation, Wuhan University of Science and Technology, Wuhan 430081, China. ligongfa@wust.edu.cn.
authors.forename: Gongfa
authors.initials: G
authors.lastname: Li
authors.affiliation: School of Machinery and Automation, Wuhan University of Science and Technology, Wuhan 430081, China. sunying6505@hotmail.com.
authors.forename: Ying
authors.initials: Y
authors.lastname: Sun
authors.affiliation: School of Machinery and Automation, Wuhan University of Science and Technology, Wuhan 430081, China. 15697188659@wo.com.cn.
authors.forename: Jianyi
authors.initials: J
authors.lastname: Kong
authors.affiliation: School of Machinery and Automation, Wuhan University of Science and Technology, Wuhan 430081, China. whjgz@wust.edu.cn.
authors.forename: Guozhang
authors.initials: G
authors.lastname: Jiang
authors.affiliation: School of Machinery and Automation, Wuhan University of Science and Technology, Wuhan 430081, China. cds20161101@163.com.
authors.forename: Heng
authors.initials: H
authors.lastname: Tang
authors.affiliation: School of Computing, University of Portsmouth, Portsmouth PO1 3HE, UK. zhaojie.ju@port.ac.uk.
authors.forename: Zhaojie
authors.initials: Z
authors.lastname: Ju
authors.affiliation: School of Computing, University of Portsmouth, Portsmouth PO1 3HE, UK. hui.yu@port.ac.uk.
authors.forename: Hui
authors.initials: H
authors.lastname: Yu
authors.affiliation: School of Computing, University of Portsmouth, Portsmouth PO1 3HE, UK. honghai.liu@port.ac.uk.
authors.forename: Honghai
authors.initials: H
authors.lastname: Liu
mesh_terms: D000465:Algorithms; D005868:Gestures; D007089:Image Enhancement; D007090:Image Interpretation, Computer-Assisted; D016011:Normal Distribution; D010363:Pattern Recognition, Automated
keywords: Gibbs Energy; image segmentation; min-cut/max-flow algorithm; sparse representation