RETRACTED ARTICLE: Detection & recognition of veiled and unveiled human face on the basis of eyes using transfer learning

Face detection and recognition are the most substantial research areas in computer vision and transfer learning due to the inspiring nature of faces as an object. In this paper, we show that we can obtain promising results on the standard face databanks when the features are extracted merely from th...

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Bibliographic Details
Published in:Multimedia tools and applications 2023, Vol.82 (3), p.4257-4287
Main Authors: Izhar, Faisal, Ali, Sajid, Ponum, Mahvish, Mahmood, Muhammad Tahir, Ilyas, Hamida, Iqbal, Amna
Format: Article
Language:English
Subjects:
Accuracy
Algorithms
Biometrics
Computer Communication Networks
Computer Science
Computer vision
Data Structures and Information Theory
Eye (anatomy)
Face recognition
Facial recognition technology
Feature extraction
Feature recognition
Histograms
Knowledge
Learning
Multimedia
Multimedia Information Systems
Pandemics
Pixels
Special Purpose and Application-Based Systems
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Summary:Face detection and recognition are the most substantial research areas in computer vision and transfer learning due to the inspiring nature of faces as an object. In this paper, we show that we can obtain promising results on the standard face databanks when the features are extracted merely from the eye. The contributions of this work are divided into three parts, specifically face detection, eyes detection and recognition for individual identification. The key features for face recognition, used in this study are the eyes, nostrils, and mouth. The key features for eyes recognition are center of left eye, center of right eye, midpoint of eyes and extraction of eyebrows. Extracted Local Binary Pattern Histogram (LBPH) method is used to extract the facial features of face images whose computational complexity is very low and these features contain simple pixel values. Furthermore, neighborhood pixels are calculated to extract effective facial feature to realize eyes recognition and person verification. This study is able to identify an individual on the basis of even a single eye. The algorithm finds the brighter eye from the face and then, on the basis of that eye, the person is identified and the name of person is provided. The experimental results of this study show that faces are recognized accurately and LBPH method has achieved 98.2% accuracy.
ISSN:1380-7501
1573-7721
DOI:10.1007/s11042-022-13402-0