A New Location Method of Touchless Knuckleprint based on Computer Vision
Xinqi Wang, Yanping Hu
Available Online April 2019.
- https://doi.org/10.2991/icmeit-19.2019.103How to use a DOI?
- feature extraction; ROI segmentation; knuckleprint location.
- The knuckleprint positioning is the key basis for the biometric recognition. This paper introduces a new location method of touchless knuckleprint based on computer vision. Firstly, in order to reduce the light impact, the RGB image is converted into YCbCr color space. We use a hybrid algorithm of elliptical model and circular gradient to segment gesture area in YCbCr color space. Subsequently, an efficient algorithm for the extraction of fingertips and finger valleys is proposed based on the distance curve, which usually takes 1 to 3 filtering operations. After obtaining the fingertips and finger valleys, the region of interest (ROI) could be located with the quadrangular window shape. Finally, because the gradient value at the knuckleprint firstly decreases to a local minimum and then increases to a local maximum, the knuckleprint could be found from the gradient curve. The method was tested on a data set of 20 people (400 hand images), and the correct rate could reach 97 percent. Experiments show that the location method of touchless knuckleprint has good effects in terms of the time complexity, space complexity and accuracy.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - CONF AU - Xinqi Wang AU - Yanping Hu PY - 2019/04 DA - 2019/04 TI - A New Location Method of Touchless Knuckleprint based on Computer Vision PB - Atlantis Press SP - 648 EP - 654 SN - 2352-538X UR - https://doi.org/10.2991/icmeit-19.2019.103 DO - https://doi.org/10.2991/icmeit-19.2019.103 ID - Wang2019/04 ER -