This thesis addresses three problems related to image registration, prediction and tracking, applied to Angiography and Oncology. For image analysis, various probabilistic models have been employed to characterize the image deformations, target motions and state estimations.
(i) In Digital Subtraction Angiography (DSA), having a high quality visualization of the blood motion in the vessels is essential both in diagnostic and interventional applications. In order to reduce the inherent movement artifacts in DSA, non-rigid image registration is used before subtracting the mask from the contrast image. DSA image registration is a challenging problem, as it requires non-rigid matching across spatially non-uniform...
Recognition of text from camera-captured scene/born-digital images help in the development of aids for the blind, unmanned navigation systems and spam filters. However, text in such images is not confined to any page layout, and its location within in the image is random in nature. In addition, motion blur, non-uniform illumination, skew, occlusion and scale-based degradations increase the complexity in locating and recognizing the text in a scene/born-digital image.
Text localization and segmentation techniques are proposed for the born-digital image data set. The proposed OTCYMIST technique won the first place and placed in the third position for its performance on...
In recent years, the electric power industry around the world is changing continuously due to transformation from regulated market structure to deregulated market structure. The main aim of the transformation of electric supply industry under open access environment is to overcome the some of the limitations faced by the vertically integrated system. It is believed that this transformation will bring in new technologies, integration of other sources of energy such as wind, solar, fuel cells, bio-gas, etc., which are self sustainable and competitive, and better choice for the consumers and so on. As a result, several new issues and challenges...
Shenoy, Ravi R
We consider real zero-crossing analysis of the real/imaginary parts of the spectrum, namely, spectral zero-crossings (SZCs). The two major contributions are to show that: (i) SZCs provide enable temporal localization of transients; and (b) SZCs are suitable for modeling transient signals. We develop a spectral dual of Kedem’s result linking temporal zero-crossing rate (ZCR) to the spectral centroid. The key requirement is stationarity, which we achieve through random-phase modulations of the time-domain signal. Transient signals are not amenable to modelling in the time domain since they are bursts of energy localized in time and lack structure. We show that the...
Renewable energy sources normally require power converters to convert their energy into standardized regulated ac output. The motivation for this thesis is to design and control power converters for renewable energy systems to ensure very good power quality, efficiency and reliability. The renewable energy sources considered are low voltage dc sources such as photovoltaic (PV) modules. Two transformer-isolated power circuit topologies with input voltage of less than 50V are designed and developed for low and medium power applications. Various design and control issues of these converters are identified and new solutions are proposed.
For low power rating of a few hundred...
We address the problem of image denoising for additive white Gaussian noise (AWGN), Poisson noise, and Chi-squared noise scenarios. Thermal noise in electronic circuitry in camera hardware can be modeled as AWGN. Poisson noise is used to model the randomness associated with photon counting during image acquisition. Chi-squared noise statistics are appropriate in imaging modalities such as Magnetic Resonance Imaging (MRI). AWGN is additive, while Poisson noise is neither additive nor multiplicative. Although Chi-squared noise is derived from AWGN statistics, it is non-additive.
Mean-square error (MSE) is the most widely used metric to quantify denoising performance. In parametric denoising approaches,...