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Face recognition approach by exploring information jointly in space, scale and orientation.

License: Apache License 2.0

MATLAB 76.99% HTML 23.01%

security-based-face-recognition's Introduction

Security-based-face-recognition

-> Objective of this project was to develop a fast and robust face recognition system that is invariant to changes such as illumination, expressions and occlusions by exploring features in image - space, scale and orientation.

-> Algorithm was based on Local Gabor binary pattern histogram sequence (LGBPHS) for improved feature matching and efficiency.

-> Used MATLAB with Image Processing Tool Box to implement the project.

Project Report:

https://github.com/vedantbhoj/Security-based-Face-Recognition/blob/master/Project%20Report.pdf

IEEE inter-college paper presentation competition:

https://github.com/vedantbhoj/Security-based-Face-Recognition/blob/master/Security%20based%20space%2Cscale%20and%20orientation%20in%20variance%20for%20human%20face%20detection.pdf

Project demo slides:

https://github.com/vedantbhoj/Security-based-Face-Recognition/blob/master/FACE%20RECOGNITION%20Final.pdf

Video Link for the Demo:

https://youtu.be/ijZ7sdxD0Xo

Refrences:

Zhen Lei, Shengcai Liao, Matti Pietikäinen, “Face Recognition by Exploring Information Jointly in Space, Scale and Orientation” IEEE TRANSACTIONS ON IMAGE PROCESSING, VOL. 20, NO. 1, JANUARY 2011.
Shufu Xie, Shiguang Shan, Xilin Chen, Jie Chen, “Fusing Local Patterns of Gabor Magnitude and Phase for Face Recognition” IEEE TRANSACTIONS ON IMAGE PROCESSING, VOL. 19, NO. 5, MAY 2010.
W. C. Zhang, S. G. Shan, W. Gao, and H. M. Zhang, “Local gabor binary pattern histogram sequence (lgbphs): A novel non-statistical model for face representation and recognition” IEEE Transaction 2005.
“Handbook of face recognition”, Li S.Z., Jain A. (Springer, 2005).
Xiaoyang Tan and Bill Triggs, “Enhanced Local Texture Feature Sets for Face Recognition Under Difficult Lighting Conditions” IEEE TRANSACTIONS ON IMAGE PROCESSING, VOL. 19, NO. 6, JUNE 2010.
B. Zhang, S. Shan, X. Chen, and W. Gao, “Histogram of gabor phase patterns (hgpp): A novel object representation approach for face recognition” IEEE Trans. Image Process., vol. 16, no. 1, pp. 57–68, Jan. 2007.

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