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- Title
A Binary Object Detection Pattern Model to Assist the Visually Impaired in detecting Normal and Camouflaged Faces.
- Authors
Sajini, S.; Pushpa, B.
- Abstract
This study presents a novel Binary Object Detection Pattern Model (BODPM) to detect objects with face key points and recognize them using the KERAS dataset. The proximity and accuracy of the recognized items were evaluated using computer vision techniques. The object recognition time interval and duration were recorded and stored permanently in a database, and the information was communicated to the visually impaired user as voice output. The normal face, without wearing a mask, was identified using binary patterns with proximity detection. Camouflaged objects were detected in a maximum probability range of 100%. The proposed method was tested, calculating accuracy and score, and compared with existing models, showcasing remarkable performance. The proposed method of normal and camouflage detection is a novel prediction with proximity analysis of objects in a frame.
- Subjects
PEOPLE with visual disabilities; COMPUTER vision; RECOGNITION (Psychology); DATABASES; RECORD stores; OBJECT recognition (Computer vision); FUSIFORM gyrus
- Publication
Engineering, Technology & Applied Science Research, 2024, Vol 14, Issue 1, p12716
- ISSN
2241-4487
- Publication type
Article
- DOI
10.48084/etasr.6631