An improved face recognition method using Local Binary Pattern method

    Research output: Chapter in Book/Report/Conference proceedingConference Paper published in Proceedings

    Abstract

    Security system based on biometrics is becoming more popular everyday as a part of safety and security measurement against all kind of crimes. Among several kinds of biometric security systems, face recognition is one of the most popular one. It is one of the most accurate, mostly used recognition methods in modern world. In this paper, two most popular face recognition methods have been discussed and compared using average image on Yale database. To reduce calculation complexity, all training and test images are converted into gray scale images. The whole face recognition process can be divided into two parts face detection and face identification. For face detection part, Viola Jones face detection method has been used out of several face detection methods. After face detection, face is cropped from the actual image to remove the background and the resolution is set as 150×150 pixels. Eigenfaces and fisherfaces methods have been used for face identification part. Average images of subjects have been used as training set to improve the accuracy of identification. Both methods are investigated using MATLAB to find the better performance under average image condition. Accuracy and time consumption has been calculated using MATLAB code on Yale image database. In future, this paper will be helpful for further research on comparison of different face recognition methods using average images on different database.
    LanguageEnglish
    Title of host publicationProceedings of 2017 11th International Conference on Intelligent Systems and Control, ISCO 2017
    PublisherIEEE, Institute of Electrical and Electronics Engineers
    Pages112-118
    Number of pages7
    ISBN (Electronic)9781509027170
    ISBN (Print)9781509027187
    DOIs
    StatePublished - 2017
    Event2017 11th International Conference on Intelligent Systems and Control, ISCO 2017 - Coimbatore, India
    Duration: 5 Jan 20176 Jan 2017

    Conference

    Conference2017 11th International Conference on Intelligent Systems and Control, ISCO 2017
    CountryIndia
    CityCoimbatore
    Period5/01/176/01/17

    Fingerprint

    Face recognition
    Face Recognition
    Face Detection
    Binary
    Face
    Biometrics
    MATLAB
    Security systems
    Eigenface
    Image Database
    Crime
    Pixel
    Safety
    Pixels

    Cite this

    Saleh, S. A., Azam, S., Yeo, K. C., Shanmugam, B., & Kannoorpatti, K. (2017). An improved face recognition method using Local Binary Pattern method. In Proceedings of 2017 11th International Conference on Intelligent Systems and Control, ISCO 2017 (pp. 112-118). [7855964] IEEE, Institute of Electrical and Electronics Engineers. DOI: 10.1109/ISCO.2017.7855964
    Saleh, Sheikh Ahmed ; Azam, S. ; Yeo, K.C. ; Shanmugam, B. ; Kannoorpatti, K./ An improved face recognition method using Local Binary Pattern method. Proceedings of 2017 11th International Conference on Intelligent Systems and Control, ISCO 2017. IEEE, Institute of Electrical and Electronics Engineers, 2017. pp. 112-118
    @inproceedings{c5d822ff7d6a434d8a7c05ce97294b47,
    title = "An improved face recognition method using Local Binary Pattern method",
    abstract = "Security system based on biometrics is becoming more popular everyday as a part of safety and security measurement against all kind of crimes. Among several kinds of biometric security systems, face recognition is one of the most popular one. It is one of the most accurate, mostly used recognition methods in modern world. In this paper, two most popular face recognition methods have been discussed and compared using average image on Yale database. To reduce calculation complexity, all training and test images are converted into gray scale images. The whole face recognition process can be divided into two parts face detection and face identification. For face detection part, Viola Jones face detection method has been used out of several face detection methods. After face detection, face is cropped from the actual image to remove the background and the resolution is set as 150×150 pixels. Eigenfaces and fisherfaces methods have been used for face identification part. Average images of subjects have been used as training set to improve the accuracy of identification. Both methods are investigated using MATLAB to find the better performance under average image condition. Accuracy and time consumption has been calculated using MATLAB code on Yale image database. In future, this paper will be helpful for further research on comparison of different face recognition methods using average images on different database.",
    keywords = "average images, eigenfaces, face detection, face recognition, fisherfaces, Viola Jones Algorithm",
    author = "Saleh, {Sheikh Ahmed} and S. Azam and K.C. Yeo and B. Shanmugam and K. Kannoorpatti",
    note = "LY_22/03/2017: Saleh, Sheikh Ahmed is listed in Scopus as internal author OSR_27/03/2017: Saleh, Sheikh Ahmed is a student at CDU, but not a HDR student.",
    year = "2017",
    doi = "10.1109/ISCO.2017.7855964",
    language = "English",
    isbn = "9781509027187",
    pages = "112--118",
    booktitle = "Proceedings of 2017 11th International Conference on Intelligent Systems and Control, ISCO 2017",
    publisher = "IEEE, Institute of Electrical and Electronics Engineers",
    address = "United States",

    }

    Saleh, SA, Azam, S, Yeo, KC, Shanmugam, B & Kannoorpatti, K 2017, An improved face recognition method using Local Binary Pattern method. in Proceedings of 2017 11th International Conference on Intelligent Systems and Control, ISCO 2017., 7855964, IEEE, Institute of Electrical and Electronics Engineers, pp. 112-118, 2017 11th International Conference on Intelligent Systems and Control, ISCO 2017, Coimbatore, India, 5/01/17. DOI: 10.1109/ISCO.2017.7855964

    An improved face recognition method using Local Binary Pattern method. / Saleh, Sheikh Ahmed; Azam, S.; Yeo, K.C.; Shanmugam, B.; Kannoorpatti, K.

    Proceedings of 2017 11th International Conference on Intelligent Systems and Control, ISCO 2017. IEEE, Institute of Electrical and Electronics Engineers, 2017. p. 112-118 7855964.

    Research output: Chapter in Book/Report/Conference proceedingConference Paper published in Proceedings

    TY - GEN

    T1 - An improved face recognition method using Local Binary Pattern method

    AU - Saleh,Sheikh Ahmed

    AU - Azam,S.

    AU - Yeo,K.C.

    AU - Shanmugam,B.

    AU - Kannoorpatti,K.

    N1 - LY_22/03/2017: Saleh, Sheikh Ahmed is listed in Scopus as internal author OSR_27/03/2017: Saleh, Sheikh Ahmed is a student at CDU, but not a HDR student.

    PY - 2017

    Y1 - 2017

    N2 - Security system based on biometrics is becoming more popular everyday as a part of safety and security measurement against all kind of crimes. Among several kinds of biometric security systems, face recognition is one of the most popular one. It is one of the most accurate, mostly used recognition methods in modern world. In this paper, two most popular face recognition methods have been discussed and compared using average image on Yale database. To reduce calculation complexity, all training and test images are converted into gray scale images. The whole face recognition process can be divided into two parts face detection and face identification. For face detection part, Viola Jones face detection method has been used out of several face detection methods. After face detection, face is cropped from the actual image to remove the background and the resolution is set as 150×150 pixels. Eigenfaces and fisherfaces methods have been used for face identification part. Average images of subjects have been used as training set to improve the accuracy of identification. Both methods are investigated using MATLAB to find the better performance under average image condition. Accuracy and time consumption has been calculated using MATLAB code on Yale image database. In future, this paper will be helpful for further research on comparison of different face recognition methods using average images on different database.

    AB - Security system based on biometrics is becoming more popular everyday as a part of safety and security measurement against all kind of crimes. Among several kinds of biometric security systems, face recognition is one of the most popular one. It is one of the most accurate, mostly used recognition methods in modern world. In this paper, two most popular face recognition methods have been discussed and compared using average image on Yale database. To reduce calculation complexity, all training and test images are converted into gray scale images. The whole face recognition process can be divided into two parts face detection and face identification. For face detection part, Viola Jones face detection method has been used out of several face detection methods. After face detection, face is cropped from the actual image to remove the background and the resolution is set as 150×150 pixels. Eigenfaces and fisherfaces methods have been used for face identification part. Average images of subjects have been used as training set to improve the accuracy of identification. Both methods are investigated using MATLAB to find the better performance under average image condition. Accuracy and time consumption has been calculated using MATLAB code on Yale image database. In future, this paper will be helpful for further research on comparison of different face recognition methods using average images on different database.

    KW - average images

    KW - eigenfaces

    KW - face detection

    KW - face recognition

    KW - fisherfaces

    KW - Viola Jones Algorithm

    UR - http://www.scopus.com/inward/record.url?scp=85015067556&partnerID=8YFLogxK

    U2 - 10.1109/ISCO.2017.7855964

    DO - 10.1109/ISCO.2017.7855964

    M3 - Conference Paper published in Proceedings

    SN - 9781509027187

    SP - 112

    EP - 118

    BT - Proceedings of 2017 11th International Conference on Intelligent Systems and Control, ISCO 2017

    PB - IEEE, Institute of Electrical and Electronics Engineers

    ER -

    Saleh SA, Azam S, Yeo KC, Shanmugam B, Kannoorpatti K. An improved face recognition method using Local Binary Pattern method. In Proceedings of 2017 11th International Conference on Intelligent Systems and Control, ISCO 2017. IEEE, Institute of Electrical and Electronics Engineers. 2017. p. 112-118. 7855964. Available from, DOI: 10.1109/ISCO.2017.7855964