Affiliation:
1. SEC Technologies , s.r.o, 1. mája 4269, 031 01 Liptovský Mikuláš , Slovakia , tel. +421911307378
Abstract
Abstract
In the case of real-time image processing, it is necessary to determine the computational complexity of the mathematical operations used. Reduction of computational complexity of 2D discrete convolution can be achieved by using a separable convolution. In this article, we focus on the application of a canny edge detector for different types of images. The main goal was to speed up the process of applying the kernel matrix to a given image using a separable convolution. By applying a separable convolution, we compared the duration of the Gaussian filter application, edges detection and the Hysteresis threshold level. Applying a separable convolution should speed up the duration of the 2D Gaussian filter as well as the edge detection. The main variable that interested us was time, but an important factor in the application of the filter and edge detection is the number of operating cycles. The use of a separable convolution should significantly reduce the number of computational cycles and reduces the duration of filter application and detection.
Reference28 articles.
1. [1] BENHAMZA, K. ‒ SERIDI, H.: “Canny edge detector improvement using an intelligent ants routing”, Evolving Systems 12, pp. 397–406, 2021.10.1007/s12530-019-09299-0
2. [2] SHRIVAKSHAN, G. T. ‒ CHANDRASEKAR, C.: “A Comparison of various Edge Detection Techniques used in Image Processing“, International Journal of Computer Science Issues, 2012.
3. [3] QIN, X.: “A modified Canny edge detector based on weighted least squares”, Comput Stat 36, pp.641–659, 2021.10.1007/s00180-020-01017-8
4. [4] AL-HAFIZ, F. ‒ AL-MEGREN, S. ‒ KURDI, H.: “Red blood cell segmentation by thresholding and Canny detector”, Procedia Computer Science, vol. 141, pp. 327-334, 2018.10.1016/j.procs.2018.10.193
5. [5] KAZEMI, M. F. ‒ MAZINAN, A. H.: “Neural network based CT-Canny edge detector considering watermarking framework”, Evolving Systems, Springer, 2021.10.1007/s12530-021-09369-2
Cited by
1 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献