摘要
针对红外热图像普遍存在的目标与背景对比度差、边缘模糊等特点,提出了一种结合图像统计特征和模糊聚类的红外图像目标提取方法对红外图像进行迭代分块,通过计算统计特征度量函数的极值来确定种子区域,进而获得红外目标约束区域。利用模糊聚类对该约束区域进行有效的聚类划分,最终实现红外图像目标提取。实验结果表明,该方法能够准确的对红外目标进行提取,便于下一步的红外目标识别与跟踪。
A novel infrared object image extraction algorithm is proposed based on statistical feature and fuzzy clustering. Seed region of infrared object and contraint containing the entire object are obtained by performing iterative blocking of image and computing the extremes of statistical feature measure function. And then, object extraction is achieved by fuzzy clustering. Experimental results verify the effectiveness and robustness of this extraction method which can facilitate the target recognition and tracking in the next step.
出处
《无线电工程》
2009年第6期26-27,33,共3页
Radio Engineering
关键词
红外图像
统计特征
模糊聚类
目标提取
infrared image
statistical feature
fuzzy clustering
object extraction
