Spatial domain entropy based local feature extraction scheme for face recognition

Fattah, Shaikh Anowarul; Islam, Md. Shafiqul; Islam, Md. Saiful

doi:10.1109/icece.2012.6471475

2012 7th International Conference on Electrical and Computer Engineering 2012

DOI: 10.1109/icece.2012.6471475

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Spatial domain entropy based local feature extraction scheme for face recognition

Shaikh Anowarul Fattah

Md. Shafiqul Islam

Md. Saiful Islam

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2017

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“…[4] Entropy measures the randomness of the pixels, which is used to characterize the texture of the input image [11].…”

mentioning

confidence: 99%

An Approach to Face Recognition Using Feed Forward Neural Network

Sajetha¹,

Gh²

2017

IJCATR

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Many approaches have been proposed for face recognition but there are major constraints like illumination, lightning, pose etc., when taken into consideration, results in poor recognition rate. We propose a method to improve the recognition rate of the face recognition system which uses various methods like homogeneity, energy, covariance, contrast, asymmetry, correlation, mean, standard deviation, entropy, kurtosis to extract the facial features for a better recognition rate. Also the extracted features are trained and it is associated with a feed forward back propagation neural network used for classification to render better results.

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“…[4] Entropy measures the randomness of the pixels, which is used to characterize the texture of the input image [11].…”

mentioning

confidence: 99%

An Approach to Face Recognition Using Feed Forward Neural Network

Sajetha¹,

Gh²

2017

IJCATR

View full text Add to dashboard Cite

show abstract

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Spatial domain entropy based local feature extraction scheme for face recognition

Cited by 1 publication

References 9 publications

An Approach to Face Recognition Using Feed Forward Neural Network

An Approach to Face Recognition Using Feed Forward Neural Network

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