基于图像分割的局部色盲矫正方法  

Partial Rectification Method of Color Blindness Based on Image-Segmentation

作　　者：何志良[1] 詹佩真 李嘉樱 蔡家荣 曾晓铭 张昕[1] HE Zhi-Liang ZHAN Pei-Zhen LI Jia-Ying CAI Jia-Rong ZENG Xiao-Ming ZHANG Xin(College of Mathematics and Informatics, South China Agriculture University, Guangzhou 510642, China)

机构地区：[1]华南农业大学数学与信息学院,广州510642

出　　处：《计算机系统应用》2017年第3期209-213,共5页Computer Systems & Applications

基　　金：2015年广东省创新创业基金(201510564287)

摘　　要：为提高红绿色盲患者对色彩的分辨能力,提出一种基于图像分割的局部色盲矫正方法.首先研究了色盲图像的仿真方法,然后结合K-means和系统聚类算法对原图像进行分割,并计算各个区域在色盲图像下LAB颜色空间中的欧氏距离作为颜色相似性的度量,确定红绿色盲难以分辨的颜色区域,最后将该区域替换成亮度一致且颜色区分度大的颜色,从而实现色盲图像矫正的目的.基于Matlab平台对算法进行验证,结果表明:该方法能够改善红绿色盲患者对颜色的分辨能力,同时在减少对颜色的认知偏差方面优于已有的方法.In order to improve red-green color blindness＇ ability of distinguishing colors, this paper introduces a partial rectification of color blindness based on image-segmentation. An emulation method of color blindness is studied first; then the original image is segmented by K-means cluster algorithm and Hierarchical cluster algorithm. Then, it calculates Euclidean distances of each region in LAB Color Space as the metric of color similarity, and confirms which color regions are hard to distinguish by red-green colorblindness. Finally, the region is replaced by other color with the same brightness and a higher degree of differentiation. With the test of the algorithm on Matlab platform, the result shows that this method can improve color blindness＇ ability to distinguish colors and it performs better than other existing methods in reducing cognitive deviation of color.

关 键 词：色盲仿真 局部矫正 K-MEANS聚类 颜色相似性 亮度因子 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]