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Multiscale Corner Detection of Gray Level Images Based on Log-Gabor Wavelet Transform

机译：基于Log-Gabor小波变换的灰度图像多尺度角点检测

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摘要

This paper presents a novel corner detection method for gray level images based on log-Gabor wavelet transform (WT). The input image is decomposed at multiscales and along multi-orientations. The magnitudes of the decomposition are formulated into the second moment matrix. The smaller eigenvalue of the second moment matrix is used as the "cornerness" measurement. Compared with the most famous Harris detector, SUSAN detector and the recently published detector - Gabor wavelet transform based detector, the proposed method shows good localization and single response to the higher order corner structures. The simulation results also shows the higher detection rate of the proposed method
机译：本文提出了一种新的基于log-Gabor小波变换（WT）的灰度图像角点检测方法。输入图像以多尺度和多方向分解。分解幅度被公式化为第二矩矩阵。第二矩矩阵的较小特征值用作“角”测量。与最著名的哈里斯检测器，SUSAN检测器和最近发布的检测器-基于Gabor小波变换的检测器相比，该方法显示了良好的定位性，并对高阶拐角结构具有单一响应。仿真结果还表明，该方法具有较高的检测率。

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