NDLI: Image quality assessment model based on features and applications in face recognition

Content Provider	IEEE Xplore Digital Library
Author	Xiao-hua Chen Chun-zhi Li
Copyright Year	2011
Description	Author affiliation: School formation & Engineering, Huzhou Teachers College, Huzhou, 313000 China (Xiao-hua Chen; Chun-zhi Li)
Abstract	Facial appearance changes because uncontrolled variations of facial appearances due to illumination, pose, expression, occlusion of non-cooperative subjects and subject-to-camera distance need to be handled to allow for successful recognition. This paper presents a novel image quality assessment model. The model is designed to reduce the influence which is caused by the degradation of facial image quality due to uncontrolled variations of facial appearances, and the degradation can lower the recognition performance. The model assesses the image quality from several aspects: (I) Occlusion measure. (II) Face-to-camera distance measure. (Ill) Pose and expression measure.(IV) Uneven illumination measure. Then noisy score is calculated by the image quality assessment model while higher noisy score's images will be discarded for face recognition, the superior face images are selected by image quality assessment model to obtain best recognition result. Experimental results on CAS-PEAL face databases with varied uncontrolled facial appearances demonstrated that the proposed approach achieved satisfactory recognition rate.
Starting Page	1
Ending Page	4
File Size	309682
Page Count	4
File Format	PDF
ISBN	9781457708930
e-ISBN	9781457708947
DOI	10.1109/ICSPCC.2011.6061709
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-09-14
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Optical filters Databases Face recognition Lighting Image Quality Assessment Model Feature Extraction Feature extraction Face Noise measurement Face Recognition
Content Type	Text
Resource Type	Article

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