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Since 20th century generation, image segmentation has been attached great importance by the people and thousands of the segmentation algorithms have been proposed. In practice, in order to facilitate research and analysis of the images that often only needs to be interested in certain parts of the image part is divided into a certain properties of a particular area, in order to use the target further,...
We propose a new method for modeling the detector module crystal positioning-blur and mis-positioning errors based on the detector modules' flood histograms (crystal position map) and crystal segmentation maps and use simulations for validation. First, a statistical simulation tool is used to simulate signal pathways from gamma photons in crystals to photo-multiplier tube pulses and then to digitized...
Salient region-based image retrieval is one of the hotspots in the domain of content-based image retrieval; however the metrics about region saliency is not in the uniform frame. The research on visual attention has shown that the factors including color, texture, scale and position influence on visual perception mostly. Consequently, the algorithm of salient region extraction is proposed by using...
As a critical unit of computer vision (CV) based applications, image segmentation is quite worth studying. Hybrid method of spatial credibilistic clustering and particle swarm optimization (SCCPSO) is a novel effective segmentation method. It's proved to produce better results than other common methods. In this paper, SCCPSO is further investigated by discussing several key points such as membership...
The Edge-Preserving Surface Estimation based on statistical jump regression analysis is a powerful approach for image denoising. However, it requires an accessorial corner-preserving technique in which a corner threshold needs to be tuned. In this paper, we suggest a novel procedure based on local segmentation using Normalized Cuts which can well preserve the edges and corners at the same time without...
Automatic video object segmentation and tracking is a challenging problem. In this paper, we introduce a new systematic method for fully automatic object segmentation and tracking using probabilistic fuzzy c-means and Gibbs random fields. The spatial segmentation is based on probabilistic fuzzy c-means clustering and Gibbs sampling. The obtained segmented mask is then refined by taking into account...
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