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A FACE RECOGNITION USING LINEAR-DIAGONAL BINARY GRAPH PATTERN FEATURE EXTRACTION METHOD
- Publication Year :
- 2023
- Publisher :
- Zenodo, 2023.
-
Abstract
- Face recognition is one the most interesting topic in the field in computer vision and image processing. Face recognition is a processing system that recognizes and identifies individuals human by their faces. Automatic face recognition is powerful way to provide, authorized access to control their system. Face recognition has many challenging problems (like face pose, face expression variation, illumination variation, face orientation and noise) in the field of image analysis and computer vision. This method is work on feature extraction part of face recognition. New way to extract face feature using LD-BGP code operator it is like LGS and LBP feature extraction operator. In our LD-BGP-code operator work in two direction first linear then diagonal. In both direction, its create eight digits code to every pixel of image. Means of these two directional are taken so that is cover all neighbor of center pixel. First linear direction, only horizontal and vertical pixel are taken. Second diagonal direction only diagonal pixels taken. In matching phase, we use Euclidean distance to match a face image. We perform the Linear and diagonal directional operator method on face database ORL. We get accuracy 95.3 %. LD-BGP method also works on different type image like illuminated and expression variation image.
- Subjects :
- Pixel
business.industry
Feature extraction
Diagonal
ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION
Binary number
020207 software engineering
Pattern recognition
02 engineering and technology
Facial recognition system
Euclidean distance
Object-class detection
0202 electrical engineering, electronic engineering, information engineering
Graph (abstract data type)
020201 artificial intelligence & image processing
Computer vision
Artificial intelligence
business
Mathematics
Subjects
Details
- Database :
- OpenAIRE
- Accession number :
- edsair.doi.dedup.....c021ce4d6579eb97a8b47f9a000edde5
- Full Text :
- https://doi.org/10.5281/zenodo.7649285