2nd International Workshop on New Approaches for


Multidimensional Signal Processing


NAMSP 2021

Technical University of Sofia, Sofia, Bulgaria

July 08-10, 2021

Plenary Speakers


Prof. Abdel-Badeeh M. Salem, Prof. of Computer Science, Faculty of Computer and Information Sciences, Head of Artificial Intelligence and Knowledge Engineering Research Labs, Ain Sham University, Egypt, E-mail: abmsalem@yahoo.com, absalem@cis.asu.edu.eg


Title of Lecture:

Machine learning for biometric recognition based on fusion of finger and dorsal hand veins
Mona A. Ahmed and Abdel-Badeeh M. Salem


Abstract: Biometric authentication can be classified into unimodel and smart multimodal biometric systems (SMBS). Unimodal systems that use single biometric trait for recognition purposes; and suffers a several practical problems like non-universality, noisy sensor data, intra-class variation, restricted degree of freedom, unacceptable error rate, failure-to-enroll and spoof attacks. So, the performance of single biometric system needs to be improved. On the other side, intelligent techniques of SMBS can offer a feasible method to solve the problems coming from unimodal biometric system. SMBS makes use of different biometric traits simultaneously to authenticate a person's identity. Robustness and high security of authentication can be achieved by using the SMBS. So, these systems achieve high recognition accuracy.
This talk presents a comprehensive analysis for the multimodal of recognition techniques and systems. The presentation reveals a new multimodal biometric system using intelligent computing technique to authenticate human by fusion of finger and dorsal hand veins pattern. We developed an image analysis technique to extract region of interest (ROI) from finger and dorsal hand veins image. After extracting ROI we design a sequence of preprocessing steps to improve finger and dorsal hand veins images using Median filter, Wiener filter and Contrast Limited Adaptive Histogram Equalization (CLAHE) to enhance vein image. Our smart technique is based on the following intelligent algorithms, namely; principal component analysis (PCA) algorithm for feature extraction and k-Nearest Neighbors (K-NN) classifier for matching operation. The database chosen was the Shandong University Machine Learning and Applications - Homologous Multi-modal Traits (SDUMLA-HMT) and Bosphorus Hand Vein Database. The achieved result for the fusion of both biometric traits was Correct Recognition Rate (CRR) is 96.8%.


Biographical Notes: Prof. Abdel-Badeeh Salem is a full Professor of Computer Science since 1989 at Faculty of Science, Ain Shams University, Egypt. His research includes intelligent computing, biomedical informatics, and intelligent e-learning, knowledge engineering, big data analytics and Biometrics. He has published around 500 papers (103 of them in Scopus). He has been involved in more than 550 International conferences and workshops as; a keynote and plenary speaker, member of Program Committees, workshop/invited session organizer, Session Chair and Tutorials.. In addition he was a member of many international societies. In addition he is a member of the Editorial Board of 50 international and national Journals Also, He is member of many Int. Scientific Societies and associations Elected member of Euro Mediterranean Academy of Arts and Sciences, Greece. Member of Alma Mater Europaea of the European Academy of Sciences and Arts, Belgrade and European Academy of Sciences and Arts, Austria. Member of international Engineering and Technology Institute - (IETI) , Hong Kong , May 2018.Member of Board of Trustees of Crown University Intl. Chartered Inc. (Ghana, Americas and partner campuses worldwide). E-mail: abmsalem@yahoo.com, absalem@cis.asu.edu.eg