International Journal of Computational Vision and Robotics
- Editor in Chief
- Prof. Srikanta Patnaik
- ISSN online
- ISSN print
- 6 issues per year
- CiteScore 1.1 (2021)
IJCVR is an international refereed journal in the field of image processing, pattern recognition, machine vision and image understanding, providing an international forum for professionals, engineers and researchers.
Topics covered include
- Early vision, vision systems
- Computer vision, AI applications
- Computer games and animation
- Computational geometry
- Shape/range/motion analysis
- Signal/image processing
- Image matching, medical imaging
- Pattern/face recognition
- Architecture, languages
- Parallel computer vision
- Interactive computational models
- Biological vision, alternative eyes
- 3D vision/perception
- Robotics, multi-sensory data fusion
IJCVR aims to provide an international forum for all scientists and engineers engaged in research and development activities in the field of machine vision, robotics, cognition and perception. IJCVR publishes various articles comprising of innovations, comparisons, extensions and new applications.
IJCVR offers a forum to help academics, researchers, R&D personnel, consultants and manufacturers in the field of computer vision, robotics and intelligent systems to disseminate information and to learn from each other's work.
IJCVR reports various intelligent and soft computing techniques in the areas of image processing and pattern recognition. This also encourages the researchers to integrate various techniques of computer vision with robotics, image understanding and cognitive science. Special Issues devoted to important topics in the areas image processing, pattern recognition, machine vision and image understanding will also be published periodically.
IJCVR is indexed in:
- Scopus (Elsevier)
- Compendex [formerly Ei] (Elsevier)
- Academic OneFile (Gale)
- ACM Digital Library
- cnpLINKer (CNPIEC)
- DBLP Computer Science Bibliography
- Expanded Academic ASAP (Gale)
- Google Scholar
- Info Trac (Gale)
- ProQuest Advanced Technologies Database with Aerospace
IJCVR is listed in:More journal lists/directories...
Editor in Chief
- Patnaik, Srikanta, SOA University and Interscience Institute of Management and Technology, Bhubaneswar, India
- Jia, Jiancheng (Kevin), International Game Technology, USA
- Shi, Junsheng, Yunnan Normal University, China
Editorial Board Members
- Bendjenna, Hakim, University of Larbi Tebessi, Algeria
- Bhatia, Sanjiv K., University of Missouri - St. Louis, USA
- Chaudhuri, Debasis, Defence Electronics Applications Laboratory, India
- Damper, R.I., University of Southampton, UK
- DeSouza, Guilherme N., University of Western Australia, Australia
- Gini, Maria, University of Minnesota, USA
- Governi, Lapo, University of Florence, Italy
- Han, Wang, Nanyang Technological University, Singapore
- Koshizen, Takamasa, Honda Research Institute Japan Co. Ltd., Japan
- Kothari, Ravi, IBM Research - India, India
- Kountchev, Roumen Kirilov, Technical University of Sofia, Bulgaria
- Krim, Hamid, North Carolina State University, USA
- Lee, Chan-Su, Yeungnam University, South Korea
- Lima, Pedro U., Instituto Superior Técnico, Puerto Rico
- Mata, Mario, Universidad Europea de Madrid, Spain
- Michalewicz, Zbigniew, University of Adelaide, Australia
- Moreno, Luis, University of Carlos III, Spain
- Nahvi, Ali, K.N. Toosi University of Technology, Iran
- Ranjan, Jayanthi, Institute of Management Technology (IMT), India
- Ruichek, Yassine, University of Technology of Belfort-Montbéliard, France
- Samal, Ashok, University of Nebraska-Lincoln, USA
- Sethi, Ishwar, Oakland University, USA
- Shafazand, M. Hassan, Shahid Bahonar University of Kerman, Iran
- Sharma, Rajeev, Pennsylvania State University, USA
- Sun, Yu, Michigan State University, USA
- Tan, Kok Kiong, National University of Singapore, Singapore
- Wren, Christopher R., Mitsubishi Electric Research Laboratories, USA
- Yang, Yeon-Mo, Kumoh National Institute of Technology, South Korea
- Yeasin, Mohammed, University of Memphis, USA
- Yezzi, Anthony, Georgia Institute of Technology, USA
- Yin, Peng-Yeng, National Chi Nan University, Taiwan
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.
The eyes have it
5 May, 2022
A regular eye examination is a solid part of maintaining eye health allowing problems to be identified sooner rather than later. Part of such an examination will commonly involve checking the lens of the eye as well as the interior of the eye. Recording a digital image of the light-sensitive retina at the back of the eye is frequently used by ophthalmologists, optometrist and others to detect vascular disorders, such as diabetic retinopathy, evidence of glaucoma, age-related macular degeneration, and optic neuritis. One of the issues with using computers to analyse a retinal image is to ensure the precise localisation of the optic disc within the retinal image in the computer so that features can be compared more accurately and problems be detectable by software with fewer false positives or false negatives for pathologies and other concerns. A new Open Access paper, published in the International Journal of Computational Vision and Robotics, describes a JAYA algorithm that performs with 99 per cent accuracy in localising the optic disc within the retinal image It uses a novel fitness function to do so. This new system performs better than other methods previously reported in the scientific literature based on tests with a publicly available database of retinal images [...]More details...
Turning over a diseased leaf
3 March, 2022
The visual and tactile examination of plant leaves is a standard method for identifying disease in crops and horticultural products. However, such an approach can be highly subjective and is dependent on the skills of the examiners. Writing in the International Journal of Computational Vision and Robotics, a team from Egypt describes a new approach to plant leaf disease detection using deep learning on a mobile device. The team's tests against a standard database of diseased leaf images showed their system to be capable of up to 98 percent diagnostic accuracy. The process is rapid and showcases the sophisticated computational power available in modern mobile phones for this kind of intensive task. Shaheera A. Rashwan and Marwa K. Elteir of the Informatics Research Institute at the City of Scientific Research and Technological Applications in Alexandria, suggest that for busy farmers in remote regions with no immediate access to plant disease experts, a mobile application that can help them spot disease and so treat the crops in a timely manner could be vital to their ongoing agricultural viability [...]More details...