@article{Soleiamni_Ahmadi_2020, title={Fast Minutia-based Palmprint Matching Using CNN and Generalized Hough Transform}, volume={5}, url={https://openjournals.uwaterloo.ca/index.php/vsl/article/view/1655}, abstractNote={<p>Due to the large number of minutiae in a palmprint, the match-<br>ing process between two palm images is time consuming. One<br>way to address this issue is aligning all palmprint images to a ref-<br>erence image. In this paper, using convolutional neural network<br>(CNN) and generalized Hough transform (GHT), we propose a new<br>method to find the corresponding rotation and displacement be-<br>tween any palmprint and the reference palm image. Furthermore,<br>the proposed method is capable of distinguishing between left and<br>right palmprint automatically which helps to speed up the match-<br>ing process. The proposed registration method followed by minutia-<br>cylinder code (MCC) matching algorithm has been evaluated on the<br>THUPALMLAB database, and the results show the superiority of our<br>algorithm over most of the state-of-the-art.</p>}, number={1}, journal={Journal of Computational Vision and Imaging Systems}, author={Soleiamni, Hossien and Ahmadi, Mohsen}, year={2020}, month={Jan.}, pages={1} }