Research on the Finger Knuckle Print Recognition Method Based on Improved Canny Operator
- https://doi.org/10.2991/acsr.k.191223.037How to use a DOI?
- canny, the finger knuckle print, ROI, daptive median filtering
In order to improve the accuracy of the classification and classification of the finger knuckle print, a method based on the improved Canny operator for the edge detection of the Finger Knuckle Print image is proposed. Firstly, the region of interest (ROI) of the Finger Knuckle Print is positioned. Secondly, The method optimized the edge detection of the finger knuckle print images from two aspects: traditional Canny algorithm filtering, gradient direction. For the poor performance of Gauss filter used by traditional Canny algorithm in limitation of removing gauss noise and loss of edge details, Adaptive median filtering is used instead of Gaussian filtering for filtering. For the problem that the Canny algorithm is easy to detect the false edge, the edge was refined by adding the direction gradient template in the process of calculating the gradient direction of the image. Finally, information entropy is used to illustrate the effectiveness of the algorithm. Compared with traditional operators, this method has better stability and robustness.
- © 2019, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Xiufeng Zhang AU - Wei Wang AU - Qiang Ding AU - Tianyi Ma AU - Chunyang Hao PY - 2019 DA - 2019/12/24 TI - Research on the Finger Knuckle Print Recognition Method Based on Improved Canny Operator BT - Proceedings of the 2019 International Conference on Big Data, Electronics and Communication Engineering (BDECE 2019) PB - Atlantis Press SP - 160 EP - 163 SN - 2352-538X UR - https://doi.org/10.2991/acsr.k.191223.037 DO - https://doi.org/10.2991/acsr.k.191223.037 ID - Zhang2019 ER -