This study compares the performances of different classification schemes and fusion techniques for target differentiation and localization of commonly encountered features in indoor robot environments using sonar sensing. Differentiation of such features is of interest for intelligent systems in a variety of applications such as system control based on acoustic signal detection and identification, map-building,…
In this dissertation, a novel scheme performing 3D reconstruction of a scene from a 2D video sequence is presented. To this aim, first, the trajectories of the salient features in the scene are determined as a sequence of displacements via Kanade-Lukas-Tomasi tracker and Kalman filter. Then, a tentative camera trajectory with respect to a metric…
In this thesis, a number of novel watermarking techniques for different 3D representations are presented. A novel watermarking method is proposed for the mono-view video, which might be interpreted as the basic implicit representation of 3D scenes. The proposed method solves the common flickering problem in the existing video watermarking schemes by means of adjusting…
The task of segmentation and tracking of objects in a video sequence is an important high-level video processing problem for object-based video manipulation and representation. This task involves utilization of many low-level pre-processing tasks such as image segmentation and motion estimation. It is also very important to assess the performance of the video object segmentation…
We propose a technique for the problem of detecting the very presence of hidden messages in an audio object. The detector is based on the characteristics of the denoised residuals of the audio file. Our proposition is established upon the presupposition that the hidden message in a cover object leaves statistical evidence that can be…
We categorize comprehensively image quality measures, extend measures defined for gray scale images to their multispectral case, and propose novel image quality measures. The statistical behavior of the measures and their sensitivity to various kinds of distortions, data hiding and coding artifacts are investigated via Analysis of Variance techniques. Their similarities or differences have been…
are involved until the development of Sequential Monte Carlo techniques which are also known as the particle filters. In particle filtering, the problem is expressed in terms of state-space equations where the linearity and Gaussianity requirements of the Kalman filtering are generalized. Therefore, we need information about the functional form of the state variations. In…
