Face Recognition Based on Histogram Equalization and LBP Algorithm
In the recent time bioinformatics take wide field in image processing. Face recognition which is basically the task of recognizing a person based on its facial image. It has become very popular in the last two decades, mainly because of the new methods developed and the high quality of the current visual instruments. There are different types of face recognition algorithms, and each method has a different approach to extract the image features and perform the matching with the input image.
In this paper the Local Binary Patterns (LBP) was used, which is a particular case of the Texture Spectrum model, and powerful feature for texture classification. The face recognition system consists of recognizing the faces acquisition from a given data base via two phases. The most useful and unique features of the face image are extracted in the feature extraction phase. In the classification the face image is compared with the images from the database.
The proposed algorithm for face recognition in this paper adopt the LBP features encode local texture information with default values. Apply histogram equalization and Resize the image into 80x60, divide it to five blocks, then Save every LBP feature as a vector table.
Matlab R2019a was used to build the face recognition system. The Results which obtained are accurate and they are 98.8% overall (500 face image).
. Xiwei Dong, Fei Wu1 and Xiao-Yuan Jing, 2018, “Generic Training Set based Multimanifold Discriminant Learning for Single Sample Face Recognition”, KSII transactions on internet and information systems vol. 12, no. 1.
. TS Vishnu Priya, G.Vinitha Sanchez, N.R.Raajan , 2018, “ Facial Recognition System Using Local Binary Patterns(LBP)”, International Journal of Pure and Applied Mathematics Volume 119 No. 15, http://www.acadpubl.eu/hub/ Special Issue.
. [Mohammed Abdulameer Aljanabi , Zahir M. Hussain , 2018 , “An Entropy-Histogram Approach for ImageSimilarity and Face Recognition” , HindawiMathematical Problems in Engineering,. https://doi.org/10.1155/2018/9801308
. Junkai Chen, Zenghai Chen, 2018 , “Facial Expression Recognition in Video with Multiple Feature Fusion”, IEEE Transactions on Affective Computing, Volume: 9 , Issue: 1.
. Raheem Ogla, Abdulmohssen J Abdul Hussien, 2017 , “Face Detection by Using OpenCV's Viola-Jones Algorithm based on coding eyes”, Iraqi Journal of Science, , Vol. 58, No.2A.
. Di Huang, Caifeng Shan, Mohsen Ardebilian, 2011, “Local Binary Patterns and Its Application to Facial Image Analysis: A Survey”, IEEE transactions on systems, man, and cybernetics—part c: applications and reviews, vol. 41, no. 6, nov. https://liris.cnrs.fr/Documents/Liris-5004.pdf
. [Yueqi Duan, Jiwen Lu, 2018, “Context-Aware Local Binary Feature Learning for Face Recognition”, IEEE Transactions on Pattern Analysis and Machine Intelligence, Volume: 40 , Issue: 5.
. Priya, T. V., Sanchez, G. V., & Raajan, N. R. (2018). Facial Recognition System Using Local Binary Patterns (LBP). International Journal of Pure and Applied Mathematics, 119(15), 1895-1899.
. Ammad A., Shah H., Farah H., Sajid H., & M. F. K.2012. “Face Recognition with Local Binary Patterns”. Bahria University Journal of Information & Communication Technology Vol. 5, 1999-4974.
. Liu, L., Fieguth, P., Zhao, G., Pietikäinen, M., & Hu, D. 2016. Extended local binary patterns for face recognition. Information Sciences, 358, 56-72.
. Ahonen, T., Hadid, A., & Pietikäinen, M. 2004. Face recognition with local binary patterns. In European conference on computer vision (pp. 469-481). Springer, Berlin, Heidelberg.
. https://towardsdatascience.com/face-recognition-how-lbph-works-90ec258c3d6b reached on 15/4/2019
. https://en.wikipedia.org/wiki/Scale-invariant_feature_transform reached on 15/4/2019
. https://en.wikipedia.org/wiki/Speeded_up_robust_features reached on 15/4/2019
How to Cite
Authors retain copyright
The use of a Creative Commons License enables authors/editors to retain copyright to their work. Publications can be reused and redistributed as long as the original author is correctly attributed.
- The researcher(s), whether a single or joint research paper, must sell and transfer to the publisher (the Academic Journal of Nawroz University) through all the duration of the publication which starts from the date of entering this Agreement into force, the exclusive rights of the research paper/article. These rights include the translation, reuse of papers/articles, transmit or distribute, or use the material or parts(s) contained therein to be published in scientific, academic, technical, professional journals or any other periodicals including any other works derived from them, all over the world, in English and Arabic, whether in print or in electronic edition of such journals and periodicals in all types of media or formats now or that may exist in the future. Rights also include giving license (or granting permission) to a third party to use the materials and any other works derived from them and publish them in such journals and periodicals all over the world. Transfer right under this Agreement includes the right to modify such materials to be used with computer systems and software, or to reproduce or publish it in e-formats and also to incorporate them into retrieval systems.
- Reproduction, reference, transmission, distribution or any other use of the content, or any parts of the subjects included in that content in any manner permitted by this Agreement, must be accompanied by mentioning the source which is (the Academic Journal of Nawroz University) and the publisher in addition to the title of the article, the name of the author (or co-authors), journal’s name, volume or issue, publisher's copyright, and publication year.
- The Academic Journal of Nawroz University reserves all rights to publish research papers/articles issued under a “Creative Commons License (CC BY-NC-ND 4.0) which permits unrestricted use, distribution, and reproduction of the paper/article by any means, provided that the original work is correctly cited.
- Reservation of Rights
The researcher(s) preserves all intellectual property rights (except for the one transferred to the publisher under this Agreement).
- Researcher’s guarantee
The researcher(s) hereby guarantees that the content of the paper/article is original. It has been submitted only to the Academic Journal of Nawroz University and has not been previously published by any other party.
In the event that the paper/article is written jointly with other researchers, the researcher guarantees that he/she has informed the other co-authors about the terms of this agreement, as well as obtaining their signature or written permission to sign on their behalf.
The author further guarantees:
- The research paper/article does not contain any defamatory statements or illegal comments.
- The research paper/article does not violate other's rights (including but not limited to copyright, patent, and trademark rights).
This research paper/article does not contain any facts or instructions that could cause damages or harm to others, and publishing it does not lead to disclosure of any confidential information.