The DOI matches its Crossref record; 25 of the 26 references it cites were found in a registry or an index.
Integer-based accurate conversion between RGB and HSV color spaces
Overview
Integrity signals
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Cites
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Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“The latest version introduces significant improvements in architecture and training methods, making it versatile choice for a wide range of computer vision tasks, especially in complex and dynamic environments like public transport vehicles [69,76].”
From A Review of Passenger Counting in Public Transport Concepts with Solution Proposal Based on Image Processing and Machine Learning (2024) · cites this paper as [69]
In the citing paper
“The YOLO v11 model [69] provides a compromise between precision and time of evaluation.”
From A Review of Passenger Counting in Public Transport Concepts with Solution Proposal Based on Image Processing and Machine Learning (2024) · cites this paper as [69]
Citations
Cites
Smith, A. R. (1978) · ACM SIGGRAPH Computer Graphics · doi:10.1145/965139.807361 · Cited by 927
Smith, A. R. (1978) · Proceedings of the 5th annual conference on Computer graphics and interactive techniques · doi:10.1145/800248.807361 · Cited by 859
Perceptually uniform color spaces for color texture analysis: an empirical evaluation
Paschos, G. (2001) · IEEE Transactions on Image Processing · doi:10.1109/83.923289 · Cited by 310
HSV color space based segmentation of region of interest in satellite images
Ganesan, P., Rajini, V., Sathish, B. S., & Shaik, K. B. (2014) · International Conference on Control, Instrumentation, Communication and Computational Technologies · doi:10.1109/iccicct.2014.6992938 · Cited by 63
An efficient detection method for rare colored capsule based on RGB and HSV color space
Liu, F., Liu, X., & Yi, C. (2014) · IEEE International Conference on Granular Computing (GrC) · doi:10.1109/grc.2014.6982830 · Cited by 36
Poynton, C. A. (1997) · Cited by 35
A fog level detection method based on image HSV color histogram
Liu, C., Lu, X., Ji, S., & Geng, W. (2014) · IEEE International Conference on Progress in Informatics and Computing · doi:10.1109/pic.2014.6972360 · Cited by 35
Rashno, A., Sadri, S., & SadeghianNejad, H. (2015) · CSI International Symposium on Artificial Intelligence and Signal Processing · doi:10.1109/aisp.2015.7123522 · Cited by 33
Poynton, C. A. (1995) · SMPTE Advanced Motion Imaging Conference · doi:10.5594/m00840 · Cited by 33
2013 IEEE International Conference on Granular Computing (GrC)
(2013) · doi:10.1109/grc32075.2013 · Cited by 24
Robust Image Chroma-Keying: A Quadmap Approach Based on Global Sampling and Local Affinity
Wang, W., & Zhao, J. (2015) · IEEE Transactions on Broadcasting · doi:10.1109/tbc.2015.2419181 · Cited by 15
Automated Switching System for Skin Pixel Segmentation in Varied LightingPreprint
Chaudhary, A., & Gupta, A. (2013) · arXiv (Cornell University) · doi:10.48550/arxiv.1304.4711 · Cited by 15
A fixed-point tone mapping operation for HDR images in the RGBE format
Dobashi, T., Murofushi, T., Iwahashi, M., & Kiya, H. (2013) · Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC) · doi:10.1109/apsipa.2013.6694154 · Cited by 12
Liu, Z., Du, S.-Y., Yang, Y., & Ji, X. (2013) · Computers & Electrical Engineering · doi:10.1016/j.compeleceng.2013.01.011 · Cited by 10
Improving visibility and fidelity of underwater images using an adaptive restoration algorithm
Guo, J., Sung, C.-C., & Chang, H.-H. (2014) · MTS/IEEE OCEANS Conference (OCEANS) · doi:10.1109/oceans-taipei.2014.6964546 · Cited by 10
Robust indoor/outdoor scene classification
Raja, R. A. A., Roomi, S. M. M., & Dharmalakshmi, D. (2015) · International Conference on Advances in Pattern Recognition · doi:10.1109/icapr.2015.7050698 · Cited by 9
Multiple face detection in color images
Archana, T., Venugopal, T., & Kumar, M. P. (2015) · International Conference on Signal Processing and Communication Engineering Systems (SPACES) · doi:10.1109/spaces.2015.7058220 · Cited by 8
Continuous hand gesture recognition for English alphabets
Bhowmick, S., Talukdar, A. K., & Sarma, K. K. (2015) · International Conference on Signal Processing and Integrated Networks (SPIN) · doi:10.1109/spin.2015.7095264 · Cited by 7
Video Enhancement Methods for Monitoring Submersible Biological Resources
Chernov, V., Koljonen, J., Alander, J. T., & Bochko, V. (2013) · IFAC Proceedings Volumes · doi:10.3182/20130828-2-sf-3019.00032 · Cited by 2
Self-citationFloating to Fixed-Point Translation with Its Application to Speech-Based Emotion Recognition
Kabi, B., Sahoo, S., Samantaray, A. K., & Routray, A. (2014) · International Conference on Emerging Applications of Information Technology · doi:10.1109/eait.2014.57 · Cited by 1
Research works printed but not linked: 1
- Sarifuddin M, Missaoui Rokia. A new perceptually uniform color space with associated color similarity measure for content-based image and video retrieval. In: Proc. of ACM SIGIR 2005 workshop on multimedia information retrieval (MMIR 2005); 2005. p. 1–8.
Cited by
Manakitsa, N., Maraslidis, G. S., Moysis, L., & Fragulis, G. F. (2024) · Technologies · doi:10.3390/technologies12020015 · Cited by 286
Sun, Y., Gu, X., Sun, K., Hu, H., Xu, M., Wang, Z., Tu, K., & Pan, L. (2016) · LWT · doi:10.1016/j.lwt.2016.10.006 · Cited by 89
Real-time underwater image enhancement: a systematic review
Moghimi, M. K., & Mohanna, F. (2021) · Journal of Real-Time Image Processing · doi:10.1007/s11554-020-01052-0 · Cited by 88
Technologies and Innovative Methods for Precision Viticulture: A Comprehensive Review
Ferro, M. V., & Catania, P. (2023) · Horticulturae · doi:10.3390/horticulturae9030399 · Cited by 90
Tomato Plant Leaves Disease Classification Using KNN and PNN
Balakrishna, K., & Rao, M. K. (2019) · International Journal of Computer Vision and Image Processing · doi:10.4018/ijcvip.2019010104 · Cited by 76
Metadata
- Authors
- Chernov, V., Alander, J., & Bochko, V.
- Affiliations
- University of Vaasa (FI)
- Corresponding author
- Chernov, Vladimir
- Venue
- Computers & Electrical Engineering
- Publisher
- Elsevier BV
- Published
- 2015-08
- Volume
- 46
- Pages
- 328-337
- ISSN
- 0045-7906 (ISSN-L)
- OpenAlex
- W1163754207
- Cited by
- 172
- References
- 26
- Citations by year
- 2026: 8 · 2025: 26 · 2024: 29 · 2023: 22 · 2022: 20 · 2021: 16 · 2020: 18 · 2019: 16 · 2018: 11 · 2017: 3 · 2016: 3
- FWCI
- 2.88
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- www.elsevier.com/tdm/userlicense/1.0/ (tdm)
- Locations
- Computers & Electrical Engineering (publishedVersion)
- Topics
- Physical Sciences › Physics and Astronomy › Atomic and Molecular Physics, and Optics › Color Science and Applications
- Physical Sciences › Computer Science › Artificial Intelligence › Computer Science and Engineering
- Physical Sciences › Computer Science › Computational Theory and Mathematics › Numerical Methods and Algorithms
- Keywords
- RGB to HSV conversion, color space conversion, integer arithmetic, look-up table, color representation, computational efficiency, memory usage
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
