基于可缩放蒙版的角点检测

2021 IEEE International Conference on Smart Information Systems and Technologies (SIST) Pub Date : 2021-04-28 DOI:10.1109/SIST50301.2021.9465940

I. Kazantsev, B. Mukhametzhanova, Suvorovsky O. Yu

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引用次数: 0

摘要

考虑了用于选择二维数字图像中角结构的可伸缩掩模。遮罩是一个在图像上滑动的2D窗口，并与图像片段进行卷积。我们提出了基于沿其侧面和边缘扩展较小掩模的可缩放二维掩模模型。在这种情况下，子矩阵保持不变，新元素的生成包括重复子矩阵的元素，保留角的结构。用测试图像进行了数值实验。

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Corner Detection Based on Scalable Masks

Scalable masks for the selection of angular structures in two-dimensional (2D) digital images are considered. The mask is a 2D window sliding over the image and convolved with image fragments. We propose the model of a scalable 2D mask based on expanding smaller mask along its sides and edges. In this case, the submatrices remain unchanged, and the generation of new elements consists in repeating the elements of the submatrix, preserving the structure of the corner. Numerical experiments with test images are performed.

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2021 IEEE International Conference on Smart Information Systems and Technologies (SIST)

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