Enhancement of eye socket recognition performance using inverse histogram fusion images and the Gabor transform

The eye socket is a cavity in the skull that encloses the eyeball and its surrounding muscles. It has unique shapes in individuals. This study proposes a new recognition method that relies on the eye socket shape and region. This method involves the utilization of an inverse histogram fusion image t...

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Bibliographic Details
Published in:ETRI journal 2025, 47(1), , pp.123-133
Main Authors: Shehu, Harisu Abdullahi, Ince, Ibrahim Furkan, Bulut, Faruk
Format: Article
Language:English
Subjects:
classification
deep learning
eye socket
Gabor features
identity recognition
image matching
vector quantization
전자/정보통신공학
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Summary:The eye socket is a cavity in the skull that encloses the eyeball and its surrounding muscles. It has unique shapes in individuals. This study proposes a new recognition method that relies on the eye socket shape and region. This method involves the utilization of an inverse histogram fusion image to generate Gabor features from the identified eye socket regions. These Gabor features are subsequently transformed into Gabor images and employed for recognition by utilizing both traditional methods and deep‐learning models. Four distinct benchmark datasets (Flickr30, BioID, Masked AT & T, and CK+) were used to evaluate the method's performance. These datasets encompass a range of perspectives, including variations in eye shape, covering, and angles. Experimental results and comparative studies indicate that the proposed method achieved a significantly ( p
ISSN:1225-6463
2233-7326
DOI:10.4218/etrij.2023-0395