Palm Vein Identification based on hybrid features selection model
University of Al-Qadisiyah（卡迪西亚大学）；College of Computer Science and Information Technology（计算机科学与信息技术学院）；Liverpool John Moores University（利物浦约翰摩尔大学）；College of Computer Science（计算机科学学院）；Sheffield（谢菲尔德）
Mohammed Hamzah Abed, Ali H. Alsaeedi, Ali D. Alfoudi, Abayomi M. Otebolaku, Yasmeen Sajid Razooqi
Palm vein identification (PVI) is a modern biometric security technique used for increasing security and authentication systems. The key characteristics of palm vein patterns include, its uniqueness to each individual, unforgettable, non-intrusive and cannot be taken by an unauthorized person. However, the extracted features from the palm vein pattern are huge with high redundancy. In this paper, we propose a combine model of two-Dimensional Discrete Wavelet Transform, Principal Component Analysis (PCA), and Particle Swarm Optimization (PSO) (2D-DWTPP) to enhance prediction of vein palm patterns. The 2D-DWT Extracts features from palm vein images, PCA reduces the redundancy in palm vein features. The system has been trained in selecting high reverent features based on the wrapper model. The PSO feeds wrapper model by an optimal subset of features. The proposed system uses four classifiers as an objective function to determine VPI which include Support Vector Machine (SVM), K Nearest Neighbor (KNN), Decision Tree (DT) and Naïve Bayes (NB). The empirical result shows the proposed system Iit satisfied best results with SVM. The proposed 2D-DWTPP model has been evaluated and the results shown remarkable efficiency in comparison with Alexnet and classifier without feature selection. Experimentally, our model has better accuracy reflected by (98.65) while Alexnet has (63.5) and applied classifier without feature selection has (78.79).
PVTree: Realistic and Controllable Palm Vein Generation for Recognition Tasks
School of Computer Science and Information Engineering, Hefei University of Technology（合肥工业大学计算机与信息工程学院）；Tencent Youtu Lab（腾讯优图实验室）；Tencent WeChat Pay Lab（腾讯微信支付实验室）
MsMemoryGAN: A Multi-scale Memory GAN for Palm-vein Adversarial Purification
Chongqing Technology and Business University（重庆工商大学）；Institut Polytechnique de Paris（巴黎综合理工学院）；Chongqing University of Posts and Telecommunications（重庆邮电大学）；China University of Mining and Technology（中国矿业大学）
Neural Architecture Search based Global-local Vision Mamba for Palm-Vein Recognition
School of Computer Science and Information Engineering, Chongqing Technology and Business University（重庆工商大学计算机与信息工程学院）；SAMOVAR, Telecom SudParis, Institut Polytechnique de Paris（巴黎综合理工大学Telecom SudParis学院SAMOVAR实验室）；Chongqing University of Posts and Telecommunications（重庆邮电大学）
Extracting Region of Interest for Palm Print Authentication
Eklavya College of Engineering（埃克拉维亚工程学院）；CV Raman College of Engineering（CV拉曼工程技术与科学学院）；Institute of Technical Education & Research（技术与教育研究院）；Siksha ‘O’ Anusandhan University（Siksha 'O' Anusandhan大学）
Experimental results on palmvein-based personal recognition by multi-snapshot fusion of textural features
Department of Computer Science, University of Milan（米兰大学计算机科学系）；Department of Electrical and Electronic Engineering, University of Cagliari（卡利亚里大学电气与电子工程系）；University of Milan（米兰大学）；University of Cagliari（卡利亚里大学）
Palmprint De-Identification Using Diffusion Model for High-Quality and Diverse Synthesis
PAMI Research Group, Department of Computer and Information Science, University of Macau（PAMI研究组，计算机与信息科学系，澳门大学）；School of Electrical and Electronic Engineering, College of Engineering, Yonsei University（电气电子工程学院，延世大学）；School of Software, Nanchang Hangkong University（软件学院，南昌航空大学）；College of Computer Science, Sichuan University（计算机科学学院，四川大学）
CFVNet: An End-to-End Cancelable Finger Vein Network for Recognition
School of Cyber Science and Engineering, Southeast University（东南大学网络空间科学与工程学院）；Purple Mountain Laboratories（紫金山实验室）；University of Macao（澳门大学）；The Hong Kong University of Science and Technology（香港科技大学）
Multiple Instance Segmentation in Brachial Plexus Ultrasound Image Using BPMSegNet
University of Electronic Science and Technology of China（电子科技大学）；Institute of Electronic and Information Engineering of UESTC in Guangdong（电子科技大学广东电子信息工程研究院）；Sichuan Provincial Hospital for Women and Children（四川省妇幼保健院）
