摘要： 复杂环境下的目标匹配会受到物体缩放、旋转、遮挡及光强变化等影响，是模式识别领域的一项难题。针对该问题，提出一种基于Harris算法和改进几何哈希法的目标匹配方法。利用Harris角点提取算法检测兴趣点，通过改进的几何哈希法实现多目标匹配。实验结果表明，该方法可实现复杂环境下的目标匹配，提高匹配精度和速度。
关键词:
目标匹配,
Harris算法,
几何哈希法,
仿射不变性,
尺度不变特征变换
Abstract: It is a very important but also a tough issue to matching objects in the field of pattern recognition as objects may be influenced by themselves such as scale, rotation, obstacle and also intensity change in the process of recognition. In allusion to this problem, an object matching method based on Harris algorithm and geometric Hash algorithm is proposed. The extraction of interested point features combined with the structure information of geometric Hash algorithm is used. Experimental results show that not only it is possible for this method to match complex objects, but also the accuracy and speed are increased.
Key words:
objects matching,
Harris algorithm,
geometric Hash algorithm,
affine invariant,
Scale Invariant Feature Transform(SIFT)
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