Corner Detection Based on Improved Shearlet Transform
College of Physics and Information Engineering, Shaanxi Normal University, Xi'an 710119, China
| Abstract: | Image corners have important theoretical significance and application value in the fields of image processing and analysis, machine vision, etc., however, the existing multi-scale analysis corner detectors fail to make full use of the multi-scale and multi-direction structural information, which affects their detection accuracy and diagonal positioning ability. Based on the basic principle of shear wave transform, the limitations of multi-scale and multi-direction image decomposition are analyzed, and the scale function is improved to the Butterworth type with a relatively flat falling edge, and then a new non-zero integrable function is obtained for the auxiliary function, and then a new multi-scale and multi-directional image decomposition method based on improved shear wave is proposed. Experimental results show that the proposed method not only partially improves the small-scale texture effect obtained after multi-scale image decomposition, but also solves the problem of large difference and messy texture between the previous small-scale local image and the original image of the clipping wave, and the image reconstruction effect is also improved and has strong robustness. In the field of image corner detection, the algorithm can make full use of multi-scale and multi-direction structural information to improve the positioning accuracy of image corner detection, reduce the error detection and missed detection rate, and has good robustness. |
| Keywords: | Shearlet; Multiscale Image Decomposition; Corner Detection |
| DOI: | 10.57237/j.cst.2025.03.002 |
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Received: 8 June 2025
Accepted: 8 August 2025
Published Online: 9 September 2025
References
| [1] | Wang M, Sun C, Sowmya A. Complex shearlets and rotary phase congruence tensor for corner detection [J]. Pattern Recognition, 2022, 128(8): 108606-108606. |
| [2] | Raas A, Sg A. Comparative Analysis of Eight Direction Sobel Edge Detection Algorithm for Brain Tumor MRI Images [J]. Procedia Computer Science, 2022, 201(1): 487-494. |
| [3] | 张阳, 刘缠牢, 卢伟家, 等. 基于 LoG 算子的双滤波边缘检测算法 [J]. 电子测量技术, 2019(4): 95-98. |
| [4] | Aishwarya N, Thangammal C B. Visible and infrared image fusion using DTCWT and adaptive combined clustered dictionary [J]. Infrared Physics and Technology, 2018, 93: 300-309. |
| [5] | Do M N, Vetterli M. The contourlet transform: An efficient directional multi-resolution image representation [J]. IEEE Transactions on Image Processing, 2005, 14(12): 2091-2106. |
| [6] | Duan C, Wang S, Huang Q, et al. Feature level MRI fusion based on 3D dual tree compactly supported Shearlet transform [J]. Journal of Visual Communication and Image Representation, 2019, 60(2): 319-327. |
| [7] | Duval-Poo M A, Noceti N, Odone F, et al. Scale invariant and noise robust interest points with shearlets [J]. IEEE Transactions on Image Processing, 2017, 26(6): 2853-2867. |
| [8] | Duval-Poo M A, Odone F, Vito E D. Enhancing signal discontinuities with shearlets: An application to corner detection [C] // International Conference on Image Analysis and Processing, 2015: 108-118. |
| [9] | Zhang W C, Sun C. Corner detection using multi-directional structure tensor with multiple scales [J]. International Journal of Computer Vision, 2020, 128(2): 438-459. |
| [10] | 田子怡, 李云红. 基于多尺度 Gabor 滤波器的角点检测 [J]. 国外电子测量技术, 2016, 35(7): 75-79. |
| [11] | Teng S W, Najmus Sadat R M, Lu G. Effective and efficient contour-based corner detectors [J]. Pattern Recognition, 2015, 48(7): 2185-2197. |
| [12] | 施雅琦. 基于Log-Gabor滤波器的角点检测算法及其应用 [D]. 西安: 西安电子科技大学, 2021: 52-60. |
| [13] | Wang M, Zhang W, Sun C, et al. Corner detection based on shearlet transform and multi-directional structure tensor [J]. Pattern Recognition, 2020, 103: 107299. |
| [14] | Leutenegger S, Chli M, et al. BRISK: Binary robust invariant scalable keypoints [C] // IEEE International Conference on Computer Vision, 2011: 2548-2555. |
| [15] | Chen Y S. Classifying credit ratings for Asian banks using integrating feature selection and the CPDA-based rough sets approach [J]. Knowledge-Based Systems, 2012, 26(1): 259-270. |
| [16] | Bay H, Ess A, Tuytelaars T, et al. Speeded-up robust features (SURF) [J]. Computer Vision & Image Understanding, 2008, 110(3): 346-359. |
| [17] | Kim S. Robust corner detection by image-based direct curvature field estimation for mobile robot navigation [J]. International Journal of Advanced Robotic Systems, 2012, 9(5): 700-709. |
| [18] | Zhang W C, Shui P L. Contour-based corner detection via angle difference of principal directions of anisotropic Gaussian directional derivatives [J]. Pattern Recognition, 2015, 48(9): 2785-2797. |
| [19] | Xia G S, Delon J, Gousseau Y. Accurate junction detection and characterization in natural images [J]. International Journal of Computer Vision, 2014, 106(1): 31-56. |
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