图象中目标的快速搜索算法

随着系统技术的发展，对目标识别跟踪系统的要求正朝着智能化方向发展，即要求系统具有对目标的自动捕获、自动识别和自动跟踪的能力。为此，在利用目标与背景之间的灰度分布特性的基础上，提出了一种在一定的范围内能自动搜索并锁定目标的目标搜索算法。该算法假定搜索过程是在一个较大的区域开始进行的，而目标仅是该区域内一个在灰度上与背景有差别的小区域。由于这个假定是符合实际情况的，因此该搜索算法可以看作是一个简单的主动边界方法，它首先由一个收缩算法逐步缩小搜索区域，再结合图象的梯度信息来搜索目标，最后锁定目标轮廓。该算法在搜索过程中只对少数的控制点进行计算，而且对控制点的初始位置无严格限制，因而可以在含有目标的区域快速完成搜索过程，实验结果表明，该算法对不同大小、不同形状的目标都可以取得很好的搜索结果。

A Fast Search Method for Target in Image

With the development of the target identification and tracking system,it is very necessary to realize the automatic capture, identification and tracking of the target. In this paper, a target searching algorithm is proposed. The algorithm takes the advantage of the gray level distributions and it automatically searches for the target inside a given region. We suggest that the searching begins at a given region, which contains the target and there are gray level differences between the target and the surrounding backgronds. Such suggestion is valid and the algorithm can be regarded as an active boundary method. At first, it reduces the searching area gradually and it locates the target with the gray level gradient information of the image, at last the boundary of the target is located. During the searching process, only few control points are computed and the initial positions of the control points are not limited strictly. Therefore it can search quickly. The experiment results are satisfactory for the targets with different size and shapes.