An Improved Local Binary Patterns Histograms Technique for Face Recognition for Real Time Applications
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 f...
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| Published in | International journal of recent technology and engineering Vol. 8; no. 2S7; pp. 524 - 529 |
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| Format | Journal Article |
| Language | English |
| Published |
05.09.2019
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| Online Access | Get full text |
| ISSN | 2277-3878 2277-3878 |
| DOI | 10.35940/ijrte.B1098.0782S719 |
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| Summary: | 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. |
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| ISSN: | 2277-3878 2277-3878 |
| DOI: | 10.35940/ijrte.B1098.0782S719 |