军用靶图上的弹孔，成象后可被认为是灰度背景上的一些斑点，这样，对这些弹孔的检测就归结为在图象中寻找单独或重叠点的问题，而这些点迹可被认为是只具有灰度特性，而没有纹理和其他内在细节的斑点，针对重叠弹孔识别较困难的问题，为了在计算量增加不大的情况下，确保子弹孔检测的可靠性，提出了一种基于模型的序列弹孔检测算法。该算法不仅可对灰度背景中的斑点进行描述和定位，而且可以适用于不同灰度、不同尺寸和背景斑点的检测，因此可将这一方法用于弹孔的识别，同时根据靶图的实际情况，还引入反馈的机制，因而取得了很好的检测效果。

The visual detection of bullet holes in a target usually can be formulated as a problem of how to exactly locate in an grayscale image the isolated and overlapping spots, which are treated as image structures without inner detail and texture. In this paper a model based matching algorithm is used to deal with this problem. A non linear model is used to describe gray and position information of those spots in a grayscale background and overlapped spots can be seen as single spots with intersection. Then the model matching process is applied to search and locate isolated and overlapping spots with various sizes, gradients and backgrounds. When we use this algorithm for holes detection and recognition in a military target, according to the characteristic of the time axis distribution of bullet holes, a feed back method is used for better performance. Experiments show it works well and achieves high reliability in real environments.