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A New Fast Matching Algorithm for Angle-Adaptive Grayscale Templates

机译：一种新的角度自适应灰度模板快速匹配算法

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摘要

Aiming at the problem that the existing gray-based template matching algorithm is not resistant to rotation and slow operation, combined with fast Fourier algorithm and image pyramid search strategy, a new fast matching algorithm for angle-adaptive grayscale templates was designed. Firstly, the image is preprocessed to reduce the noise interference during matching. Secondly, the multi-angle to-be-detected gallery is built by rotating the sub-image to be matched, which solves the problem of contour artifact caused by template rotation. Finally, the FFT-based NCC algorithm is used to measure the similarity. Combined with the image pyramid search strategy and the indented search step method, the computational complexity is reduced and the robustness is improved. And this algorithm is compared with the traditional anti-rotation algorithm during experiments. Experiments show that the proposed method achieves good results when the angle deviation is large and the image matching probability is low or mismatched.
机译：针对现有的灰色模板匹配算法不抵抗旋转和慢速操作的问题，与快速傅里叶算法和图像金字塔搜索策略相结合，设计了一种新的快速匹配算法，用于角度自适应灰度模板。首先，预处理图像以减少匹配期间的噪声干扰。其次，通过旋转要匹配的子图像来构建多角度的待检测的廊，其解决了由模板旋转引起的轮廓伪像的问题。最后，使用基于FFT的NCC算法来测量相似性。结合图像金字塔搜索策略和缩进的搜索步骤方法，减少了计算复杂性并且改善了鲁棒性。并将该算法与实验期间的传统防旋转算法进行了比较。实验表明，当角度偏差大并且图像匹配概率低或不匹配时，该方法达到了良好的结果。

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