基于改进K均值聚类分析的迷彩伪装色选取

伪装色是影响迷彩伪装效果的关键因素。提出一种基于改进K均值聚类分析的迷彩伪装色选取算法：在Lab颜色空间中选择色差尽可能大的标准伪装色作为初始聚类中心，由最小色差原则和相邻元素特征共同决定目标像素归属，最后将得到的背景优势色（最优聚类中心）转换为军标规定的迷彩伪装色。通过迷彩伪装图案设计实例对伪装色选取算法进行了实验分析，并通过边缘检测和识别跟踪算法对不同背景下的目标迷彩伪装效果进行了验证。结果表明，基于改进K均值聚类分析的迷彩伪装色选取方法能够满足迷彩图案具备较好伪装效果的要求。

Camouflage color selection based on improved K-means clustering

Camouflage color is the greatest factor in camouflage pattern with good background matching.An effective method for camouflage color selection based on improved K -means clustering is presented in this paper.Standard camouflage colors with great differences are selected as initial centroids,and pixels partition depends on color difference with cluster centroids and neighbors character,at last the background superior colors are transformed into standard camouflage colors ordained by army.Combining the above-...