In this paper we describe an experiment where we studied empirically and in depth the application of a global adaptive color space to be used in the similarity function of an established region-growing color image segmentation algorithm. To perform this experiment we chose the Mumford-Shah energy functional and the Mahalanobis distance metric. The objective was to test the approach empirically ...

In this paper, we investigate the load balancing problem by jointly considering sectorization and hybrid F/CDMA scheme in the scenario of non-uniform traffic distributions. The problem is formulated as a mathematical optimization model, and is solved by Lagrangean relaxation approach. The model objective is to minimize weighted blocking probability in terms of distribution diversity. To evaluat...

In this paper, we investigate the load balancing problem by jointly considering sectorization and hybrid F/CDMA scheme in the scenario of non-uniform traffic distributions. The problem is formulated as a mathematical optimization model, and is solved by Lagrangean relaxation approach. The model objective is to minimize weighted blocking probability in terms of distribution diversity. To evaluat...

In this paper, we propose a robust adaptive region segmentation algorithm for noisy images, within a Bayesian framework. A multiresolution implementation of the algorithm is performed using a wavelets basis and can be used to process both 2D and 3D data. In this work we focus on the adaptive character of the algorithm and we discuss how global and local statistics can be utilised in the segment...

In real-time content-oriented video applications, fast unsupervised object segmentation is required. This paper proposes a real-time unsupervised object segmentation that is stable throughout large video shots. It trades precise segmentation at object boundaries for speed of execution and reliability in varying image conditions. This interpretation is most appropriate to applications such as su...

Recent technological advances have contributed to the advent of phase contrast magnetic resonance imaging (PCMRI) as standard practice in clinical environments. In particular, decreased scan times have made using the modality more feasible. PCMRI is now a common tool for flow quantification, and for more complex vector field analyses that target the early detection of problematic flow condition...

BACKGROUND AND PURPOSE It is known that fluorine-18 fluorodeoxyglucose PET/computed tomography (CT) segmentation algorithms have an impact on the metabolic tumor volume (MTV). This leads to some uncertainties in PET/CT guidance of tumor radiotherapy. The aim of this study was to investigate the effect of segmentation algorithms on the PET/CT-based MTV and their correlations with the gross tumor...

PURPOSE To develop and validate a fully automatic region-of-interest (ROI) delineation method for on-line adaptive radiotherapy. METHODS AND MATERIALS On-line adaptive radiotherapy requires a robust and automatic image segmentation method to delineate ROIs in on-line volumetric images. We have implemented an atlas-based image segmentation method to automatically delineate ROIs of head-and-nec...

Color image segmentation is a crucial step in many computer vision and pattern recognition applications. This article introduces an adaptive and unsupervised clustering approach based on Vorono¨ı regions, which can be applied to solve the color image segmentation problem. The proposed method performs region splitting and merging within Vorono¨ı regions of the Dirich-let Tessellated image (also ...

Image retrieval based on region is one of the most promising and active research directions in recent year's CBIR, while region segmentation, feature selection and feature extraction of region are key issues. However, the existing approaches always adopt a uniform approach of segmentation and feature extraction for all images in the same system. In this paper, we propose adaptive image segmenta...