In this paper we present a new framework for image segmentation using probabilistic multinets. We apply this framework to integration of regionbased and contour-based segmentation constraints. A graphical model is constructed to represent the relationship of the observed image pixels, the region labels and the underlying object contour. We then formulate the problem of image segmentation as the...

Electronic mail is one of the important communication channels of information technology which serves across the globe. Though the functionalities of e-mail have been very helpful in serving both individuals and institutions, it encounters a major issue called ‘Spamming’. Spam mails are unwanted text or image-based messages, often sent without the consent of users so as to fill their mailboxes....

Wavelet-domain hidden Markov tree (HMT) model has been recently proposed and applied to image processing, e.g., image segmentation. A new multiscale image segmentation method, called HMTseg, was proposed by Choi and Baraniuk using the waveletdomain HMT. In this paper, we study the HMTseg algorithm and investigate the Contextual Labeling Tree which is used for the context-based Bayesian intersca...

N.A. Ofodile 1 , S. M. Sani 2 PhD, MSc(Eng), BSc(Hons)Eng 1 (NAF Research and Development Centre, Air Force Institute of Technology, Nigeria) 2 (Department of Electrical and Electronics Engineering, Nigerian Defence Academy, Nigeria) _____________________________________________________________________________________ Abstract: This paper presents the implementation as well as simulated results...

Vocal tract magnetic resonance imaging (MRI) has become one of the preferred imaging modalities for the analysis of human speech production. However, the raw image data must be segmented before further analysis can take place. This paper describes a hybrid approach to extract a 3D tongue model from 3D or 2D MRI scans of the vocal tract during speech, which combines unsupervised image segmentati...

This paper provides new hybrid medical image segmentation based on Global Minimization by Active Contour (GMAC) method and Spatial Fuzzy C Means Clustering method (SFCM) tailored to CT imaging applications. GMAC is the unification of image segmentation and image denoising, which is a combination of snake, Rudin-Osher denoising and the Mumford Shah model. Here globalization of contour is applied...

Biometric identification systems recognize persons by a digital signature derived from a particular physiological attribute. One such attribute is the unique patterns that exist in the texture of an iris. These patterns provide sufficient information to uniquely identify an individual. Segmentation of the iris texture from an acquired digital image is not always accurate the image contains nois...

Barrett's mucosa is one of the most important diseases in upper gastrointestinal system that caused by gastro-esophagus reflux. If left untreated, the disease will cause distal esophagus and gastric cardia adenocarcinoma. The malignancy risk is very high in short segment Barrett's mucosa. Therefore, lesion area segmentation can improve specialist decision for treatment. In this paper, we propos...

A hybrid image compression method is proposed in this paper which segments the image into background and foreground and compress them with different quality levels.. The foreground of the image is given more importance than the background. An edge based segmentation method is used to segment the image into foreground area and background area. The proposed method highly preserves quality of the ...

Segmentation and counting sub-cellular structure of size range 0.1 μm to 1 μm is a very challenging problem even for medical experts. Image acquisition time for the state-of-the-art fluorescence microscopes is about 1-5 seconds. A fast and efficient method for segmentation and counting of sub-cellular structure is proposed for concurrent post-processing of fluorescence microscopy images. The pr...