[
[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
]Search in Google Scholar
[
[2] SHRIVAKSHAN, G. T. ‒ CHANDRASEKAR, C.: “A Comparison of various Edge Detection Techniques used in Image Processing“, International Journal of Computer Science Issues, 2012.
]Search in Google Scholar
[
[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
]Search in Google Scholar
[
[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
]Search in Google Scholar
[
[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
]Search in Google Scholar
[
[6] CHANDRASHEKAR, N. S. ‒ NATRAJ, K. R.: “Detection of Lung Cancer by Canny Edge Detector for Performance in Area, Latency, “, 2018 International Conference on Electrical, Electronics, Communication, Computer, and Optimization Techniques (ICEECCOT), pp. 690-696, 2018.10.1109/ICEECCOT43722.2018.9001445
]Search in Google Scholar
[
[7] NIKOLIC, M. ‒ TUBA, E. ‒ TUBA, M.: “Edge detection in medical ultrasound images using adjusted Canny edge detection algorithm,”, 24th Telecommunications Forum (TELFOR), pp. 1-4, 2016.10.1109/TELFOR.2016.7818878
]Search in Google Scholar
[
[8] ZHANG, Z. ‒ CHEN, P. ‒ SHI, X. ‒ YANG, L.: “Text-Guided Neural Network Training for Image Recognition in Natural Scenes and Medicine”, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 43, no. 5, pp. 1733-1745, 2021.
]Search in Google Scholar
[
[9] LAAROUSSI, S. ‒ BAATAOUI, A. ‒ HALLI, A. ‒ KHALID, S.: “A dynamic mosaicking method for finding an optimal seamline with Canny edge detector, “, Procedia Computer Science, vol. 148, pp. 618-626, 2019.10.1016/j.procs.2019.01.050
]Search in Google Scholar
[
[10] CHENGETA, K. ‒ VIRIRI, S.: “Image Preprocessing Techniques for Facial Expression Recognition with Canny and Kirsch Edge Detectors, “, Computational Collective Intelligence. ICCCI 2019. Lecture Notes in Computer Science, vol 11684, 2019.10.1007/978-3-030-28374-2_8
]Search in Google Scholar
[
[11] GAOCHAO, W. ‒ TSE, P. W. ‒ YUAN, M.: “Automatic internal crack detection from a sequence of infrared images with triple-threshold Canny edge detector, “, Measurement Science and Technology, 2017.
]Search in Google Scholar
[
[12] MANIKANDAN, L. C. ‒ SELVAKUMAR, R. K. ‒ NAIR, S. A. H., et al.: “Hardware implementation of fast biateral filter and canny edge detector using Raspberry Pi for telemedicine applications, “, Ambient Intell Human Comput 12, pp. 4689–4695, 2021.
]Search in Google Scholar
[
[13] ALASSMI, N. S. ‒ ZAGHLOUL, S. S.: “Speeding Up Canny Edge Detection Using Shared Memory Processing“, International Journal of New Computer Architectures and their Applications. 7.pp. 68-76. 2017.10.17781/P002313
]Search in Google Scholar
[
[14] PELLEGRINO, F. A. ‒ VANZELLA, W. ‒ TORRE, V.: “Edge Detection Revisited. IEEE transactions on systems, man, and cybernetics, “, Cybernetics: a publication of the IEEE Systems, Man, and Cybernetics, 2004.
]Search in Google Scholar
[
[15] MOGALE, H.: “High Performance Canny Edge Detector using Parallel Patterns for Scalability on Modern Multicore Processors, “, 2017.
]Search in Google Scholar
[
[16] JIN LI, C. ‒ QUA, Z. ‒ YE WANG, S. ‒ LIU, L.: “A method of cross-layer fusion multi-object detection and recognition based on improved faster R-CNN model in complex traffic environment”, Pattern Recognition Letters, vol. 145, pp. 127-134, 2021.10.1016/j.patrec.2021.02.003
]Search in Google Scholar
[
[17] MATAS, J. ‒ OBDRŽÁLEK, Š.: “Object recognition methods based on transformation covariant features”, 2004 12th European Signal Processing Conference, pp. 1721-1728, 2004.
]Search in Google Scholar
[
[18] XU, Q. ‒ VARADARAJAN, S. ‒ CHAKRABARTI, C. ‒ KARAM, L. J.: “A Distributed Canny Edge Detector: Algorithm and FPGA Implementation, “, in IEEE Transactions on Image Processing, vol. 23, no. 7, pp. 2944-2960, 2014.
]Search in Google Scholar
[
[19] GENTSOS, CH. ‒ SOTIROPOULOU, C. L. ‒ NIKOLAIDIS, S. ‒ VASSILIADIS, N.: “Real-time canny edge detection parallel implementation for FPGAs, “. pp. 499-502., 2010.10.1109/ICECS.2010.5724558
]Search in Google Scholar
[
[20] LEE, J. ‒ TANG, H. ‒ PARK, J.: “Energy Efficient Canny Edge Detector for Advanced Mobile Vision Applications,”, in IEEE Transactions on Circuits and Systems for Video Technology, vol. 28, no. 4, pp. 1037-1046, 2018.
]Search in Google Scholar
[
[21] LIN, J. ‒ GUO, T. ‒ YAN, Q. F. ‒ WANG, W.: “Image segmentation by improved minimum spanning tree with fractional differential and Canny detector”, Journal of Algorithms & Computational Technology, January 2019.10.1177/1748302619873599
]Search in Google Scholar
[
[22] YANG, Y. ‒ ZHAO, X. ‒ HUANG, M. ‒ WANG, X. ‒ ZHU, Q.: “Multispectral image based germination detection of potato by using supervised multiple threshold segmentation model and Canny edge detector, “, Computers and Electronics in Agriculture. 182.,2021.10.1016/j.compag.2021.106041
]Search in Google Scholar
[
[23] NIXON, M. S. ‒ AGUADO, A. S.: “Basic image processing operations”, Feature Extraction & Image Processing for Computer Vision (Third Edition), Editors M. S. Nixon and A. S. Aguado, ISBN 978-0-12-396549-3, pp. 83-136, 2012.10.1016/B978-0-12-396549-3.00003-3
]Search in Google Scholar
[
[24] LV, D. ‒ PAN, S.: “Improved Canny edge detection algorithm based on deep learning”, Scientific Journal of Intelligent Systems Research, vol. 3, no. 2, 2021.
]Search in Google Scholar
[
[25] SHWETHA, V. ‒ RENU MADHAVI, C. H.: “Design Techniques For Improvement Of Canny Edge Detection Algorithm”, vol. 8, no. 8, 2020.
]Search in Google Scholar
[
[26] MA, X. ‒ LI, B. ‒ ZHANG, Y. ‒ YAN, M.: “The Canny Edge Detection and Its Improvement”, Artificial Intelligence and Computational Intelligence, 4th International Conference, vol. 7530, pp. 50-58, 2012.
]Search in Google Scholar
[
[27] JIANG, X. J. ‒ SCOTT, P. J.: “Characterization of free-form structured surfaces”, Advanced Metrology, Editors X. J. Jiang and P. J. Scott, ISBN 978-0-12-821815-0, pp. 281-317, 2020.10.1016/B978-0-12-821815-0.00011-3
]Search in Google Scholar
[
[28] LI, B. ‒ SÖDERSTRÖM, U. ‒ RÉHMAN, S. U. ‒ LI, H.: “Restricted Hysteresis Reduce Redundancy in Edge Detection”, Journal of Signal and Information Processing, vol. 4, no. 3B, pp. 158-163, 2013.10.4236/jsip.2013.43B028
]Search in Google Scholar
