International Journal of Biometrics
- Editor in Chief
- Prof. Dr. Khalid Saeed
- ISSN online
- ISSN print
- 4 issues per year
- Clarivate Analytics 2022 JCI 0.1
- CiteScore 1.2 (2021)
Biometrics and human biometric characteristics form the basis of research in biological measuring techniques for the purpose of people identification and recognition. IJBM addresses the fundamental and emerging areas in computer science that deal with biological measurements. It covers both the theoretical and practical aspects of human identification and verification.
Topics covered include
- Age and gender recognition
- Anthropology/physical anthropology
- DNA, genetic inheritance
- Ear, face and iris recognition, retina
- Emotion detection
- Facial thermograms
- Fingerprints and palm prints
- Gait recognition
- Hand geometry, hand veins
- Kansei engineering
- Keystroke dynamics and mouse gestures
- Odour and taste
The key objective of IJBM is to provide the academic community with an international forum in the field of human authentication and people identity verification from both physiological and behavioural points of view. It aims to publish new insights into current and emerging innovations in computer systems and technology for biometrics development and its applications.
IJBM provides a vehicle to help professionals, academics, researchers and policy makers, working in the field biometrics to disseminate information and to learn from each other's work.
IJBM publishes original papers, review papers, technical reports, case studies, conference reports, management reports, book reviews, notes, commentaries, and news. Special Issues devoted to important topics in biometrics will occasionally be published, particularly as post-conference issues. Such issues will contain extended versions of selected papers presented at international conferences on biometrics.
IJBM is indexed in:
- Scopus (Elsevier)
- Compendex [formerly Ei] (Elsevier)
- Emerging Sources Citation Index (Clarivate Analytics)
- Academic OneFile (Gale)
- ACM Digital Library
- cnpLINKer (CNPIEC)
- DBLP Computer Science Bibliography
- Expanded Academic ASAP (Gale)
- Google Scholar
- Info Trac (Gale)
- Inspec (Institution of Engineering and Technology)
- ProQuest Advanced Technologies Database with Aerospace
IJBM is listed in:More journal lists/directories...
Editor in Chief
- Saeed, Khalid, Bialystok University of Technology, Poland
- Tadeusiewicz, Ryszard, AGH University of Science and Technology, Poland
- Gavrilova, Marina L., University of Calgary, Canada
- Nishiuchi, Nobuyuki, Tokyo Metropolitan University, Japan
- Porwik, Piotr, University of Silesia, Poland
- Raja, S.P., Vellore Institute of Technology, India
- Xiao, Qinghan, Defence Research and Development Canada – Ottawa, Canada
Editorial Board Members
- Abdulla, Waleed H., University of Auckland, New Zealand
- Abraham, Ajith, Machine Intelligence Research Labs (MIR Labs), USA
- Bakshi, Sambit, National Institute of Technology, Rourkela, India
- Bartkowiak, Anna, University of Wroclaw, Poland
- Chaki, Nabendu, University of Calcutta, India
- Choraś, Ryszard S., University of Technology and Life Sciences, Poland
- De Silva, Liyanage C., University of Brunei Darussalam, Brunei Darussalam
- Fei, Lunke, Guangdong University of Technology, China
- Feng, David Dagan, University of Sydney, Australia
- Granger, Eric, École de technologie supérieure, Canada
- Kasprzak, Włodzimierz, Warsaw University of Technology, Poland
- Khurram Khan, Muhammad, King Saud University, Saudi Arabia
- Kurzynski, Marek, Wroclaw University of Technology, Poland
- Liu, Chengjun, New Jersey Institute of Technology, USA
- Maxion, Roy A., Carnegie Mellon University, USA
- Pacut, Andrzej, Warsaw University of Technology , Poland
- Pan, Jeng-Shyang, National Kaohsiung University of Applied Sciences, Taiwan, Province of China
- Proença, Hugo, University of Beira Interior, Portugal
- Razzak, Imran, King Saud bin Abdulaziz University for Health Sciences, Saudi Arabia
- Rutkowski, Leszek, Czestochowa University of Technology, Poland
- Sinha, G.R., International Institute of Information Technology Bangalore, India
- Snášel, Václav, FEI VSB-TU Ostrava, Czech Republic
- Upadhyay, Nitin, Goa Institute of Management, India
- Wierzchoń, Sławomir, Polish Academy of Sciences, Poland
- Xu, Yong, Harbin Institute of Technology, China
- Yamaguchi, Toru, Tokyo Metropolitan University, Japan
- Yanushkevich, Svetlana, University of Calgary, Canada
- Yau, Wei-Yun, Institute for Information Research, Singapore
- Zhang, Lei, The Hong Kong Polytechnic University , Hong Kong SAR, China
- Zhou, Huiyu, Queen's University of Belfast, UK
- Zhuang, Hanqi, Florida Atlantic University, USA
A few essentials for publishing in this journal
- Submitted articles should not have been previously published or be currently under consideration for publication elsewhere.
- Conference papers may only be submitted if the paper has been completely re-written (more details available here) and the author has cleared any necessary permissions with the copyright owner if it has been previously copyrighted.
- Briefs and research notes are not published in this journal.
- All our articles go through a double-blind review process.
- All authors must declare they have read and agreed to the content of the submitted article. A full statement of our Ethical Guidelines for Authors (PDF) is available.
- There are no charges for publishing with Inderscience, unless you require your article to be Open Access (OA). You can find more information on OA here.
- All articles for this journal must be submitted using our online submissions system.
- View Author guidelines.
An algorithm that lifts the veil
8 August, 2022
Face-recognition technology is advancing apace and has applications in security and biometrics, marketing, education, criminal investigation, and many other areas, it can now not only recognise the person but can ascertain the expression on their face. Research in the International Journal of Biometrics tackles the limitations of face recognition software when the person's face is partly obscured, by a veil or protective face mask, for instance. The researchers, based in Hungary, Jordan, Saudi Arabia, the UK, and the USA report a facial recognition accuracy with their deep-learning approach that is 99.95% accurate for facial recognition even for a person wearing a niqab, which most of the face except the eyes. 99.9% accurate for gender recognition, and determination of age. It can recognise that a veiled person or person wearing a covid mask is or is not smiling, through analysis of the eyes, with 80.9% accuracy. Tests were carried out on an image database of 150 people, 41 male and 109 female subjects aged from 8 to 78 years old [...]More details...