Survey Paper | Computer Science & Engineering | India | Volume 6 Issue 7, July 2017
Periocular Biometrics for Iris Recognition: A Review
Nirgish Kumar | Komal 
Abstract: - Periocular refers to the facial region in the vicinity of the eye, including eyelids, lashes and eyebrows. While face and irises have been extensively studied, the periocular region has emerged as a promising trait for unconstrained biometrics, following demands for increased robustness of face or iris systems. With surprisingly high discrimination ability, this region can be easily obtained with existing setups for face and iris, and the requirement of user cooperation can be relaxed, thus facilitating the interaction with biometric systems. It is also available over a wide range of distances even when the iris texture cannot be reliably obtained (low resolution) or under partial face occlusion (close distances). Here, we review the state of the art in periocular biometrics research. A number of aspects are described, including i) existing databases, ii) algorithms for periocular detection and/or segmentation, iii) features employed for recognition, iv) identification of the most discriminative regions of the periocular area, v) comparison with iris and face modalities, and vi) soft-biometrics (gender/ethnicity classification),. This work is expected to provide an insight of the most relevant issues in periocular biometrics, giving a comprehensive coverage of the existing literature and current state of the art. Moreover, we will use different feature extraction techniques such as LBP, PCA, and ICA for pre-processing of periocular biometrics. Comparative Analysis with other competent technologies is also the essential part of this research work.
Keywords: Index Terms Acquisition, Biometric System, Periocular, iris recognition, iris, databases etc
Edition: Volume 6 Issue 7, July 2017,
Pages: 491 - 494
How to Cite this Article?
Nirgish Kumar, Komal, "Periocular Biometrics for Iris Recognition: A Review", International Journal of Science and Research (IJSR), Volume 6 Issue 7, July 2017, pp. 491-494, https://www.ijsr.net/get_abstract.php?paper_id=ART20175151
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