网格运动统计的刑侦现勘图像匹配算法

An image matching method for criminal investigation and scene survey based on grid motion statistics

刑侦现勘图像存在质量差、模糊、目标复杂且分辨力低等缺点,这些缺点导致图像匹配时出现效果差、耗时长等问题,针对该问题提出一种基于网格运动统计(GMS)的特征匹配算法。该算法首先使用网格对图像均匀分割,然后在网格邻域中统计额外支持特征的数量,其次分别计算正确与错误匹配的概率以构造评分函数,最后通过评分函数和评分阈值来区分正确与错误匹配。实验结果表明,该算法对刑侦现勘图像能够实现快速准确的匹配,且该算法对模糊人脸和高纹理的刑侦现勘图像都有较好的匹配效果。

There are some disadvantages in the image of criminal investigation and scene survey,such as poor quality,fuzzy,complex target and low resolution,resulting in poor effect and long time-consumption in image matching.A feature matching algorithm based on grid motion statistics(GMS)is proposed for above problems.By means of this algorithm,the image is segmented uniformly by grid,and the number of additional supporting features is counted in the grid neighborhood;then the probability of correct and wrong matching is calculated to construct the scoring function,and the correct and wrong matching is distinguished by means of the scoring function and scoring threshold.The experimental results show that the algorithm can achieve fast and accurate matching images of the criminal investigation and scene survey,and the algorithm has a certain matching effect on both fuzzy face and high-texture criminal investigation and scene survey images.