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This paper addresses the problem of recovering a super-resolved image from a single low resolution input. This is a hybrid approach of single image super resolution. The technique is based on combining an Iterative back projection (IBP) method with the edge preserving Infinite symmetrical exponential filter (ISEF). Though IBP can minimize the reconstruction(More)
The objective of voice conversion system is to formulate the mapping function which can transform the source speaker characteristics to that of the target speaker. In this paper, we propose the General Regression Neural Network (GRNN) based model for voice conversion. It is a single pass learning network that makes the training procedure fast and(More)
Identification of human based on iris has gained increased attention in recent years. The paper focuses on novel and efficient approach of partial iris based recognition of human using pupil circle region growing and binary integrated edge intensity curve which defeats the difficulties of eyelids occlusions. The experimental results are obtained on CASIA(More)
Motion blur caused by relative motion between the camera and the object being captured is an everyday situation that deteriorates the quality of the images largely. Even a photograph captured in low light conditions or that of a fast moving object undergo motion blur and cause significant degradation of the image and demands for deblurring the same to(More)
Character segmentation and recognition are imperative steps in the vehicle license plate recognition (VLPR) system. The skewed license plate affects badly on the accurate character segmentation and recognition. To solve the problem, an efficient approach for skew correction of license plate is proposed based on wavelet transform and principal component(More)
Voice Conversion is a technique which morphs the speaker dependent acoustical cues of the source speaker to those of the target speaker. Speaker dependent acoustical cues are characterized at different levels such as shape of vocal tract, glottal excitation and long term prosodic parameters. In this paper, low time and high time liftering is applied to the(More)
— Image registration is an important and fundamental task in image processing used to match two different images. Given two or more different images to be registered, image registration estimates the parameters of the geometrical transformation model that maps the sensed images back to its reference image. A feature-based approach to automated(More)
Character segmentation and detection play a very important role in the automatic license plate recognition (ALPR) system. For accurate character segmentation first need is to remove skew from the received license plate. Skew is the angle by which the image seems to be deviated from its perceived steady state position. To solve the problem, a combined(More)
In this paper an image fusion technique is developed to remove clouds from satellite images. The proposed method involves an auto associative neural network based PCAT (principal component transform) and SWT (stationary wavelet transform) to remove clouds recursively which integrates complementary information to form a composite image from multitemporal(More)