Abdelhakim Bendada

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This work introduces a new locally adaptive texture features for efficient multispectral face recognition. This new descriptor called Local Adaptive Ternary Pattern (LATP) is based on the Local Ternary Pattern (LTP). Unlike the previous techniques, this new descriptor determines the local pattern threshold automatically using local statistics. It shares(More)
Automatic face recognition (AFR) is an area with immense practical potential which includes a wide range of commercial and law enforcement applications, and it continues to be one of the most active research areas of computer vision. Even after over three decades of intense research, the state-of-the-art in AFR continues to improve, benefiting from advances(More)
Automatic face recognition is an area with immense practical potential which includes a wide range of commercial and law enforcement applications. Hence it is unsurprising that it continues to be one of the most active research areas of computer vision. Even after over three decades of intense research, the state-of-the-art in face recognition continues to(More)
In this work we present an efficient approach for physiological features extraction from infrared face images. The physiological features represent the network of blood vessels under the face skin. These networks are unique to each individual. The proposed technique permits the construction of Faceprints (similar to fingerprints) from thermal infrared(More)
This work introduces the use of LBP like texture descriptors for efficient multispectral face recognition. LBP has been widely used in visible spectrum face recognition. This work extend its use to non visible spectrums (active and passive infrared spectrums). Local Binary Pattern (LBP) and Local Ternary Pattern (LTP) descriptors are used. Also a simple(More)
Infrared thermography is a nondestructive evaluation technique in which the specimen surface is thermally stimulated to produce a temperature difference between "sound" (free of defects) areas and eventual defective regions. It is well known that the thermographic methods based on the thermal contrast are strongly affected by non-uniform heating at the(More)
In this work we present an efficient approach for physiological features extraction from near infrared images of the hand and the lower forearm-wrist region. The physiological features represent the dorsal venous network of the hand and the superficial veins in the lower forearm and wrist region. These networks are unique to each individual and can be used(More)
In the context of infrared thermographic NDT, the whole acquisition chain is first reviewed including the required pre-processing stages needed to restore images from degradations such as vignetting, camera noise and dead pixels. Polynomial conversion to temperature values is next. Secondly, the processing steps are discussed following two main directions:(More)