基于质心距离增量矩阵的曲线描述和匹配

Curve Representation and Matching Based on Centroid Distance Increment Matrix

图像中物体轮廓线的描述和辨识是图像理解的一个核心问题,提出了一种新的快速的轮廓线描述和匹配方法。该方法不是把曲线中的每一点都进行了描述和匹配,而是按照最小面积法则对曲线进行采样,用采样点与质心的距离增量为每一个采样点赋予一个身份向量,通过所有采样点的身份向量来构造曲线的质心距离增量矩阵以描述曲线,最后利用两条曲线的质心距离增量矩阵的差异度来度量它们的相似性。实验证明该描述方法不仅具有很好的唯一性,而且相比目前已有算法计算量大大减少。该方法的一个实际应用在于将一个地区的SAR图像与地图相匹配。

The extraction and recognition of boundaries from images are core problems in image understanding. In this paper, a new and quick method of irregular curve representation and matching is presented. This method does not represent and match every point of curve, rather, it samples the curve according to the principle of minimal area. Incremental distance between sample point and centroid of curve is used as status vector of sample point, then the centroid distance increment matrix is designed using these status vector of sample point. Lastly, it confirms the similarity of two curves by comparing the vectors of two curves. The experiment has shown that this method can not only exclusively represent curve, but also consumedly reduce calculation. A practical use of the proposed approach is to register a SAR image of certain region with maps.