Multiple Human Face Detection and Recognition based on LBPH and Machine Learning

Kumar, P. Nagendra; Narayan, Vashishtha; Chauhan, Divyanshu; Singh, Astha

doi:10.29027/ijirase.v4.i7.2021.817-822

Cited by 1 publication

(1 citation statement)

References 9 publications

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“…Normalize Pixel Intensity is applied before training the model, as this reduces the error in recognition as the pixel intensity will be common, these are mainly used as this will help in reducing noise in an image, so that the recognition could be faster. LBPH algorithm gives completely a unique result and obtained 86% of accuracy (Kumar et al 2021). LBPH facial feature will reduce the dimension of the histograms and also helps in increasing the calculation speed and also the recognition rate with 85 % accuracy (Xiang et al 2016).…”

Section: Discussionmentioning

confidence: 99%

Efficient System for Criminal Face Detection Technique on Innovative Facial Features To Improve Accuracy Using LBPH In Comparison With CNN

2022

pnr

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The objective of this study is to use face recognition technology to identify the suspects through facial biometrics which helps in identification of criminals faster based on innovative facial features. Innovative Local Binary Pattern Histograms algorithm is used for the face recognition method. Materials and Methods: Face detection for identifying the criminals is performed using Innovative Local Binary Pattern Histograms (N=10) was iterated 10 times for efficient and accurate analysis based on labeled data with G power in 80% and threshold 0.05%, CI 95% mean and standard deviation. The split size of training and testing of 70% and 30% respectively. Results: It is found that the accuracy of LBPH is 90.80% which is higher than the CNN model 90.30% and attained the significance value of p = 0.0303 (p<0.05). Conclusion: For the face identification purpose Local Binary Pattern Histograms algorithm is preferred than Convolutional Neural Network algorithm.

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Section: Discussionmentioning

confidence: 99%

Efficient System for Criminal Face Detection Technique on Innovative Facial Features To Improve Accuracy Using LBPH In Comparison With CNN

2022

pnr

View full text Add to dashboard Cite

show abstract

Multiple Human Face Detection and Recognition based on LBPH and Machine Learning

Cited by 1 publication

References 9 publications

Efficient System for Criminal Face Detection Technique on Innovative Facial Features To Improve Accuracy Using LBPH In Comparison With CNN

Efficient System for Criminal Face Detection Technique on Innovative Facial Features To Improve Accuracy Using LBPH In Comparison With CNN

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