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The Dynamic Tree (DT) Bayesian Network is a powerful analytical tool for image segmentation and object segmentation tasks. Its hierarchical nature makes it possible to analyze and incorporate information from different scales, which is desirable in many applications. Having a flexible structure enables model selection, concurrent with parameter inference. In this paper, we propose a novel framework,...
A scheme of segmentation based on low-level and high-level cues is presented. Firstly, image-pyramid is obtained based on segmentation by Weighted Aggregation (SWA), the suitable coarse pixel image is selected to be as low-level segmentation cues. Kernel principal component analysis (KPCA) is used for building the space of shape to represent shape prior knowledge. The coarse pixel image is expressed...
In this paper, we propose a novel approach that combines particle filter tracking and 3D graph cut based segmentation to achieve silhouette tracking against drastic scale change and occlusion. The segmentation module offers particle filter tracking procedure the target shape information to compensate spatial information loss in the histogram based particle filter tracking process. Meanwhile, particle...
Linear features such as line segments and contour fragments are important cues for object detection and scene analysis. Least square based and Hough-like approaches are quite popular and powerful. However, least square approaches are sensitive to outliers, and are unable to handle the case where there is more than one underlying line segment; while Hough-like approaches do not work well when extracting...
Aiming at the complex background of coronary angiograms, weak contrast between the coronary arteries and the background, a new segmentation method based on transition region extraction of degree is proposed. Firstly, the paper analyzes the characteristic of coronary angiograms. Secondly, 6 different Gaussian matched templates are used to enhance the coronary angiograms in order to remove the background...
Hand gestures are an important modality for human computer interaction (HCI). Compared to many existing interfaces, hand gestures have the advantages of being easy to use, natural, and intuitive. Successful applications of hand gesture recognition include computer games control, human-robot interaction, and sign language recognition, to name a few. Vision-based recognition systems can give computers...
Image segmentation has an essential role in image Analysis, pattern recognition and low-level vision. Since multiple segmentation algorithms exists in literature, numerical evaluations are needed to quantify the consistency quantification because are allowing a principled comparison between segmentation results on different images, with differing numbers of regions, and generated by different algorithms...
In this paper, we present an algorithm for automatic liver segmentation from CT scans which is based on a statistical shape model. The proposed method is a hybrid method that combines three steps: 1) Localization of the average liver shape model in a test CT volume via 3D generalized Hough transform; 2) Subspace initialization of the statistical shape model; 3) Deformation of the shape model to adapt...
Automatic segmentation of bright-field cell images is important to cell biologists, but difficult to complete due to the complex nature of the cells in bright-field images (poor contrast, broken halo, missing boundaries). Standard approaches such as level set segmentation and active contours work well for fluorescent images where cells appear as round shape, but become less effective when optical...
The objective of this work is to investigate a new approach for object segmentation in videos. While some amount of user interaction is still necessary for most algorithms in this field, these can be reducedmaking use of certain properties of graph-based image segmentation algorithms. Based on one of these algorithms a framework is proposed, that tracks individual foreground objects through arbitrary...
This work deals with the problem of automatic temporal segmentation of a video into elementary semantic units known as scenes. Its novelty lies in the use of high-level audio information in the form of audio events for the improvement of scene segmentation performance. More specifically, the proposed technique is built upon a recently proposed audio-visual scene segmentation approach that involves...
Tracking of partially occluded or unevenly illuminated objects is the most challenging problem of the analysis of moving objects. Both problems can solve the graph cut segmentation with elliptical shape prior. Interactive control is necessary in the training phase of system as well as in a critical situation requiring the human intervention. Bi-elliptical shape prior model corresponds to the anatomy...
This paper deals with experimental comparison of classical method of Graph cut segmentation with segmentation using Active contours. From methods of Active contours are chosen to comparison two methods. First method is based on classic Active contour method and second method is based on Active contours independent on gradient of the edges. Application of Graph cut segmentation allows finding the optimal...
First order saddle points have important applications in different fields of science and engineering. Some of their interesting applications include estimation of chemical reaction rate, image segmentation, path-planning and robotics navigation. Finding such points using evolutionary algorithms is a field that remains yet to be well investigated. In this paper, we present an evolutionary algorithm...
A novel method based on mixed graph structure is proposed for image representation and matching. The mixed graph structure is constructed according to the spatial relation of the regions within an image. This structure does not require redundant information to describe images. An image matching process focuses on evaluating region attributes and relationships contained in the corresponding mixed graph...
Uncertainty is one of the major challenges related to the semantic gap in multimedia data description and retrieval. It is due not only to errors and imprecisions in content classification but also to the extended range of user queries. In this paper, an extension of fuzzy conceptual graphs, suitable for handling uncertainty in visual event description and retrieval, is presented. We deal with two...
Segmentation of fingerprint image is to extract the region of interest (ROI) of image and highly influences the performance of automatic fingerprint identification system (AFIS). For each image block, either background or foreground label should be determined. In traditional methods, the label of an image block is only based on the features from this block itself such as local gray variance and local...
We propose a novel approach for satellite cloud image segmentation based on the improved Normalized Cuts Model. We extracted three important features from the multi-channel grayscale information and the texture features of satellite image, by the statistical analyses of the surface observation. Having set up the weight matrix by those features, we use the spectral graph theoretic framework of normalized...
Tumor segmentation from MRI data is an important but time consuming task performed manually by medical experts. Automating this process is challenging due to the high diversity in appearance of tumor tissue among different patients and, in many cases, similarity between tumor and normal tissue. We propose a semi-automatic interactive brain tumor segmentation system that incorporates 2D interactive...
Reliable tracking of objects is an inevitable prerequisite for automated video surveillance systems. As most object detection methods, which are based on machine learning, require adequate data for the application scenario, foreground segmentation is a popular method to find possible regions of interest. These usually require a specific learning phase and adaptation over time. In this work we will...
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