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Corner Detection Based on Gabor Filter Decomposition and Phase Congruency

Yabin Wang, Qiang Zhang, Long Wang

Abstract


Corners play an important role in many computer vision tasks, such as vision based unmanned control systems, image matching and stitching, moving target tracking and 3D reconstruction. However, because of the different focus points, images captured at the same scene often contain different resolutions. Some unsatisfied detection results for those images may be obtained by the traditional corner detectors. This paper proposes a novel corner detection method, aiming at detecting corners from images captured with different focal-lengths or different focuses. Firstly, a series of Gabor filters with different center frequencies and bandwidths are constructed. Secondly, the input image is decomposed into many sub-bands by the constructed band-pass filters. Then, the maximum phase congruency moment based corner detection algorithm is performed on each sub-band. Finally, the detected corners in the sub-band that contains the most detected points are taken as the final detection results. Experimental results demonstrate that the proposed method detects enough corners for the long focal-length images, which are usually blurry when enlarged. And for multi-focus images, the proposed method can also obtain higher repeatability rate than some existing popular detectors do.

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References


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DOI: http://dx.doi.org/10.21535%2FProICIUS.2014.v10.260

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