Human Thermal Face Recognition Based on Random Linear Oracle (RLO) Ensembles,

Citation:
Gaber, T., Alaa Tharwat, Abdelhameed Ibrahim, V. Snasel, and A. E. Hassanien, "Human Thermal Face Recognition Based on Random Linear Oracle (RLO) Ensembles,", IEEE International Conference on Intelligent Networking and Collaborative Systems, ,015, pp. 91-98 . , Taipei, Taiwan, 2-4 September , 2015.

Date Presented:

2-4 September

Abstract:

This paper proposes a human thermal face recognition approach with two variants based on Random linear
Oracle (RLO) ensembles. For the two approaches, the Segmentation-based Fractal Texture Analysis (SFTA) algorithm was used for extracting features and the RLO ensemble classifier was used for recognizing the face from its thermal image. For the dimensionality reduction, one variant (SFTALDA-RLO) was used the technique of Linear Discriminant Analysis (LDA) while the other variant (SFTA-PCA-RLO) was used the Principal Component Analysis (PCA). The classifier’s model was built using the RLO classifier during the training phase and in the testing phase then this model was used to identify the unknown sample images. The two variants were evaluated using the Terravic Facial IR Database and the experimental results showed that the two variants achieved a good recognition rate at 94.12% which is better than related work.

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