Please use this identifier to cite or link to this item: http://13.232.72.61:8080/jspui/handle/123456789/435
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dc.contributor.authorSujatha, B. M.-
dc.contributor.authorSuresh Babu, K.-
dc.contributor.authorRaja, K. B.-
dc.contributor.authorVenugopal, K. R.-
dc.date.accessioned2018-10-12T05:34:30Z-
dc.date.available2018-10-12T05:34:30Z-
dc.date.issued2015-10-
dc.identifier.citationSujatha, B. M., Suresh Babu, K., Raja, K. B., & Venugopal, K. R. (2015). Hybrid domain based face recognition using DWT, FFT and compressed CLBP. International Journal of Image processing (IJIP), 9(5), 283-303.en_US
dc.identifier.issn1985-2304-
dc.identifier.urihttp://13.232.72.61:8080/jspui/handle/123456789/435-
dc.description.abstractThe characteristics of human body parts and behaviour are measured with biometrics, which are used to authenticate a person. In this paper, we propose Hybrid Domain based Face Recognition using DWT, FFT and Compressed CLBP. The face images are preprocessed to enhance sharpness of images using Discrete Wavelet Transform (DWT) and Laplacian filter. The Compound Local Binary Pattern (CLBP) is applied on sharpened preprocessed face image to compute magnitude and sign components. The histogram is applied on CLBP components to compress number of features. The Fast Fourier Transformation (FFT) is applied on preprocessed image and compute magnitudes. The histogram features and FFT magnitude features are fused to generate final feature. The Euclidian Distance (ED) is used to compare final features of test face images with data base face images to compute performance parameters. It is observed that the percentage recognition rate is high in the case of proposed algorithm compared to existing algorithms.en_US
dc.language.isoenen_US
dc.publisherIJIPen_US
dc.subjectElectronics Engineeringen_US
dc.subjectCommunicationen_US
dc.subjectComputer interfacesen_US
dc.subjectBiometricsen_US
dc.titleHybrid Domain based Face Recognition using DWT, FFT and Compressed CLBPen_US
dc.typeArticleen_US
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