Object tracking using log-polar transformation

In this thesis, we use log-polar transform to solve object tracking. Object tracking in video sequences is a fundamental problem in computer vision. Even though object tracking is being studied extensively, still some challenges need to be addressed, such as appearance variations, large scale and rotation variations, and occlusion. We implemented a novel tracking algorithm which works robustly in the presence of large scale changes, rotation, occlusion, illumination changes, perspective transformations and some appearance changes. Log-polar transformation is used to achieve robustness to scale and rotation. Our object tracking approach is based on template matching technique. Template matching is based on extracting an example image, template, of an object in first frame, and then finding the region which best suites this template in the subsequent frames. In template matching, we implemented a fixed template algorithm and a template update algorithm. In the fixed template algorithm we use same template for the entire image sequence, where as in the template update algorithm the template is updated according to the changes in object image. The fixed template algorithm is faster; the template update algorithm is more robust to appearance changes in the object being tracked. The proposed object tracking is highly robust to scale, rotation, illumination changes and occlusion with good implementation speed

Automatic Image Mosaicing using Harris Corner Detector

Mosaicing is a computer-vision-based approach to produce high field of view with best image quality. It is the process of generating a single, large, joined image by combining the visual options from multiple images .Image mosaics are set of overlapping images together with coordinate transformations regarding the different image coordinate systems. By applying the appropriate transformations via a warping operation and merging the overlapping regions of warped images, it is possible to build a single image covering the entire visible area of the scene. The proposed algorithm for Image Mosaicing using Harris Corner Detector and template matching for automatic control points’ selection has been discussed. The implementation section of the algorithm is discussed along with test results. The merits and demerits of the algorithms have been analyzed. We have used our own image datasets for experimenting. DOI: 10.17762/ijritcc2321-8169.15071

XRound : A reversible template language and its application in model-based security analysis

Successful analysis of the models used in Model-Driven Development requires the ability to synthesise the results of analysis and automatically integrate these results with the models themselves. This paper presents a reversible template language called XRound which supports round-trip transformations between models and the logic used to encode system properties. A template processor that supports the language is described, and the use of the template language is illustrated by its application in an analysis workbench, designed to support analysis of security properties of UML and MOF-based models. As a result of using reversible templates, it is possible to seamlessly and automatically integrate the results of a security analysis with a model. (C) 2008 Elsevier B.V. All rights reserved

Incorporating Security Behaviour into Business Models Using a Model Driven Approach

There has, in recent years, been growing interest in Model Driven Engineering (MDE), in which models are the primary design artifacts and transformations are applied to these models to generate refinements leading to usable implementations over specific platforms. There is also interest in factoring out a number of non-functional aspects, such as security, to provide reusable solutions applicable to a number of different applications. This paper brings these two approaches together, investigating, in particular, the way behaviour from the different sources can be combined and integrated into a single design model. Doing so involves transformations that weave together the constraints from the various aspects and are, as a result, more complex to specify than the linear pipelines of transformations used in most MDE work to date. The approach taken here involves using an aspect model as a template for refining particular patterns in the business model, and the transformations are expressed as graph rewriting rules for both static and behaviour elements of the models

Atlas-Based Prostate Segmentation Using an Hybrid Registration

Purpose: This paper presents the preliminary results of a semi-automatic method for prostate segmentation of Magnetic Resonance Images (MRI) which aims to be incorporated in a navigation system for prostate brachytherapy. Methods: The method is based on the registration of an anatomical atlas computed from a population of 18 MRI exams onto a patient image. An hybrid registration framework which couples an intensity-based registration with a robust point-matching algorithm is used for both atlas building and atlas registration. Results: The method has been validated on the same dataset that the one used to construct the atlas using the "leave-one-out method". Results gives a mean error of 3.39 mm and a standard deviation of 1.95 mm with respect to expert segmentations. Conclusions: We think that this segmentation tool may be a very valuable help to the clinician for routine quantitative image exploitation.Comment: International Journal of Computer Assisted Radiology and Surgery (2008) 000-99