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A Fast Template Matching Method for Rotation Invariance Using Two Stage Process

机译:一种快速模板匹配方法,用于使用两个阶段过程的旋转不变性

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Template matching is a technique for finding the location of a reference image or an object inside a scene image. The conventional method of template matching uses cross correlation algorithms. The method is simple to implement and understand, but it is one of the slowest methods. Furthermore, if the object in the image is rotated, the tradition method can fail. In this paper, an algorithm for a rotation invariant template matching method is proposed. The algorithm consists of two stages process. In the first stage, the scene image and template one are reduced in resolution. Then the features of the subimage covered by the template are extracted using RPT (Ring Projection Transformation) method. The normalized correlation formula is used to select the matching candidates in the coarse search stage. These candidates will be recovered to original position and determine the searching range. In the second stage process, Zernike moments based on the matching candidates are used to determine the optimal matching point.
机译:模板匹配是用于查找参考图像或场景图像内对象的位置的技术。模板匹配的传统方法使用跨相关算法。该方法易于实现和理解,但它是最慢的方法之一。此外,如果图像中的对象旋转,则传统方法可能会失败。本文提出了一种旋转不变模板匹配方法的算法。该算法包括两个阶段过程。在第一阶段,在分辨率下减少场景图像和模板。然后使用RPT(环投影变换)方法提取由模板覆盖的子图的特征。归一化相关公式用于选择粗照搜索阶段中的匹配候选。这些候选人将恢复到原始位置并确定搜索范围。在第二阶段过程中,基于匹配候选的Zernike矩来确定最佳匹配点。

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