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Corner detection based on Blockwise self-similarity of images

机译:基于图像块的自相似性的角度检测

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摘要

We propose a novel method for corner detection based on image self-similarity. In our proposed method, first, blockwise self similarity of image is extracted in the same way as for fractal coding of gray-scale images. A corner point is detected by using the property that a fixed point of this self-affine mapping based on blockwise self-similarity is conformed to a corner point of an object contour. In order to demonstrate the efficiency of the proposed method, we applied it to snakes and utilized it to move control points of snakes. It was confirmed that the proposed method detects correct corners from real images. Also, it was confirmed that, using the proposed method, snakes extract object contours which have concavity and convexity and which are difficult to extract by conventional snakes.
机译:我们提出了一种基于图像自相似性的角落检测的新方法。 在我们所提出的方法中,首先,以与灰度图像的分形编码相同的方式提取图像的块自相似性。 通过使用基于块自相相似度的该自助映射的固定点符合对象轮廓的角点来检测角点点。 为了展示所提出的方法的效率,我们将其应用于蛇并利用它来移动蛇的控制点。 确认所提出的方法从真实图像中检测到正确的角落。 此外,证实,使用该方法,蛇提取具有凹凸性的物体轮廓,并且难以通过传统蛇提取。

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