An Improved Local Binary Patterns Histograms Technique for Face Recognition for Real Time Applications

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Abstract

Recently, face recognition and its applications has been considered as one of the image analysis most successful applications, especially over the past several years. Face Recognition is a unique system that can be used by using unique facial features for identification or verification of a person from a digital image. In a face recognition system, there are many technique that can be used. This paper provides an efficient of the Local Binary Patterns Histograms (LBPH) based technique provided by OpenCV library which is implemented in Python programming language which is well suitable for realistic scenarios. In this paper we also provide visual qualitative outcome with existing algorithm (Haar-cascade classifier and Local Binary Patterns Histograms (LBPH)). As a result, the proposed technique outperform better in terms of visual qualitative analysis.

Publisher

Blue Eyes Intelligence Engineering and Sciences Engineering and Sciences Publication - BEIESP

Subject

Management of Technology and Innovation,General Engineering

Cited by 4 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

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3. E-health in Internet of Things (IoT) in Real-Time Scenario;Proceedings of Second International Conference on Computing, Communications, and Cyber-Security;2021

4. Future of Augmented Reality in Healthcare Department;Proceedings of Second International Conference on Computing, Communications, and Cyber-Security;2021

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