Palmprint recognition using multiscale transform, linear discriminate analysis, and neural network
نویسندگان
چکیده
Palmprint recognition is gaining grounds as a biometric system for forensic and commercial applications. Palmprint recognition addressed the recognition issue using low and high resolution images. This paper uses PolyU hyperspectral palmprint database, and applies back-propagation neural network for recognition, linear discriminate analysis for dimensionality reduction, and 2D discrete wavelet, ridgelet, curvelet, and contourlet for feature extraction. The recognition rate accuracy shows that contourlet outperforms other transforms.
منابع مشابه
Palmprint Recognitionvia Bandlet, Ridgelet, Wavelet and Neural Network
Palmprint recognition has emerged as a valid biometric based personal identification tool. Palmprints with high resolution features such minutia points, ridges and singular points or low resolution features such as wrinkles and principals determine their applications. In this paper a 700nm spectral band PolyU hyperspectral palmprint database is utilized and the multiscale band let image transfo...
متن کاملPalmprint Recognition by using Bandlet, Ridgelet, Wavelet and Neural Network
Palmprint recognition has emerged as a substantial biometric based personal identification. Tow types of biometrics palmprint feature. high resolution feature that includes: minutia points, ridges and singular points that could be extracted for forensic applications. Moreover, low resolution feature such as wrinkles and principal lines which could be extracted for commercial applications. This ...
متن کاملPatterns Prediction of Chemotherapy Sensitivity in Cancer Cell lines Using FTIR Spectrum, Neural Network and Principal Components Analysis
Drug resistance enables cancer cells to break away from cytotoxic effect of anticancer drugs. Identification of resistant phenotype is very important because it can lead to effective treatment plan. There is an interest in developing classifying models of resistance phenotype based on the multivariate data. We have investigated a vibrational spectroscopic approach in order to characterize a...
متن کاملPatterns Prediction of Chemotherapy Sensitivity in Cancer Cell lines Using FTIR Spectrum, Neural Network and Principal Components Analysis
Drug resistance enables cancer cells to break away from cytotoxic effect of anticancer drugs. Identification of resistant phenotype is very important because it can lead to effective treatment plan. There is an interest in developing classifying models of resistance phenotype based on the multivariate data. We have investigated a vibrational spectroscopic approach in order to characterize a...
متن کاملPalmprint Recognition Using Deep Scattering Convolutional Network
Palmprint recognition has drawn a lot of attention during the recent years. Many algorithms have been proposed for palmprint recognition in the past, majority of them being based on features extracted from the transform domain. Many of these transform domain features are not translation or rotation invariant, and therefore a great deal of preprocessing is needed to align the images. In this pap...
متن کامل