Dattatray V. Jadhav

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This paper presents a new pattern recognition framework for face recognition based on the combination of Radon and wavelet transforms, which is invariant to variations in facial expression, and illumination. It is also robust to zero mean white noise. The technique computes Radon projections in different orientations and captures the directional features of(More)
Computer based automated system is one of the important diagnostic tools in medical field. Diabetic Retinopathy is an eye disorder in which red lesions due to blood leakages can be spotted on retinal surface. This disease is commonly observed in long term diabetic patients. Ignorance to this disease can result into permanent blindness. Early stage signs of(More)
This paper presents rotation invariant technique for iris feature extraction and fused post-classification at the decision level to improve the performance under non-ideal environmental conditions. In this work, directional iris texture features based on two-dimensional (2D) Fast Discrete Curvelet Transform (FDCT) are computed. This approach divides the(More)
This paper presents a wavelet Kernel Fisher classifier (WKFC) for face recognition. Wavelet transform is used to derive the multiresolution based desirable facial features. Three level decomposition is used to form the pyramidal multiresolution features to cope with the variations due to illumination and facial expression changes. The Kernel principal(More)
This paper presents a technique for face recognition which uses wavelet transform to derive desirable facial features. Three level decompositions are used to form the pyramidal multiresolution features to cope with the variations due to illumination and facial expression changes. The fractional power polynomial kernel maps the input data into an implicit(More)
In this paper, we have developed an algorithm which combines features from human iris and face for person verification. Iris recognition is one of the most accurate biometric modalities having verification results close to 98%. On the other hand, face is one of the most widely used biometric features because of its ease of capture. We have adapted score(More)
The image intensity surface in an ideal fingerprint image contains a limited range of spatial frequencies, and mutually distinct textures differ significantly in their dominant frequencies. This paper presents a multiresolution feature based subspace technique for fingerprint recognition. The technique computes the core point of fingerprint and crops the(More)