自动化学报2017，Vol.43Issue(4)：528-537,10.DOI:10.16383/j.aas.2017.c150862
基于改进最大类间方差法的手势分割方法研究
Gesture Segmentation with Improved Maximum Between-cluster Variance Algorithm
摘要
Abstract
In this paper,in order to solve the problem of ambiguity or unclear boundary caused by noise and interference in gesture imaging,a gesture segmentation method based on the improved maximum between-cluster variance algorithm is proposed.Firstly,a two-dimensional gray histogram of gesture image is generated,and positions of noise points are determined on the two-dimensional gray histogram.After filtering noise in the corresponding region of the gesture image,a two-dimensional gray histogram is reconstructed.The point set of the inner point area are projected to the 45 degrees line to generate the gray projection histogram.Then,the global Otsu is used to determine the left boundary of the local Otsu and Gauss function is used to get the right boundary of the local Otsu in the projection gray histogram.Finally,the local Otsu is used to segment the gesture image.This method can effectively segment the gesture image accurately.Experimental results have verified the effectiveness of the proposed algorithm.关键词
手势分割/改进最大类间方差法/二维灰度直方图/投影灰度直方图Key words
Gesture segment/improved Otsu/two-dimensional gray histogram/projection gray histogram引用本文复制引用
李擎,唐欢,迟健男,邢永跃,李华通..基于改进最大类间方差法的手势分割方法研究[J].自动化学报,2017,43(4):528-537,10.基金项目
北京市自然科学基金(4122050)资助 （4122050）
Supported by Natural Science Foundation of Beijing (4122050) （4122050）
