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We introduce a scheme for the production of LDV (Layered Depth Video) content, based on capturing from a hybrid camera system, consisting of two time of flight and five CCD cameras and introduce a post production step, based on Grab - Cut segmentation, which significantly improves the quality of the end result. The proposed improvement step can be done fully automatically, based on initialization...
This work proposes an interactive tool for creating stereo image from a mono image. The user interaction is defined as scribbling on the object of interest followed by relative depth assignment to the selected object. Initial step in the algorithm is to create structured image oversegments with intensity homogeneity and geometrical convexity constraint. The final image segmentation is realized by...
For lung tissue adhesion of the situation in the lung CT images, based on the classical watershed algorithm, this introduce line-encoded ideology, use contour tracing method to determine adhesion region segmentation points, according to segment code to get the split line, thus separating the adhesion region. Experimental results show that this method will be effective in the lung adhesion region segmentation,...
We present a new method for fully automated video matting. This method uses depth information acquired by a depth camera to automatically compute trimaps. Trimaps segment an image into three nonoverlapping regions (foreground, background, and unknown) and generation of a highly accurate trimap is one of the most important tasks in natural alpha matting. We propose an adaptive approach to generate...
An efficient depth map generation method is presented for static scenes with moving objects. Firstly, static background scene is reconstructed. Depth map of the reconstructed static background scene is extracted by linear perspective. Then, moving objects are segmented precisely. Depth values are assigned to the segmented moving objects according to their positions in the static scene. Finally, the...
In this paper, we propose a novel method that uses coordinate alignment and background pixel extraction to synthesize highly accurate and spatially consistent intermediate views from a pair of stereo images and disparity maps. In contrast to the traditional depth image-based rendering (DIBR) method, where useful background pixels are discarded in the warping process, the proposed method extracts these...
The segmentation of ultrasound images is challenging due to the difficulty of appropriate modeling of their appearance variations including speckle as well as signal dropout. We propose a novel automatic segmentation method for 2D cardiac ultrasound images based on hidden Markov models (HMMs). By directly exploiting the local image characteristics around contour points in images and integrating them...
In this paper, a real-time image segmentation algorithm is presented. It utilizes both color and depth information retrieved from a multi-sensor capture system, which combines stereo camera pairs with time-of-flight range sensor. The algorithm targets low complexity and fast implementation which can be achieved through parallelization. Applications, such as immersive videoconferencing and lecturer...
We propose a methodology for improved segmentation of images in a Bayesian framework by fusion of color, texture and gradient information. The proposed algorithm is initialized by subjecting the input image to an adaptive clustering scheme for initial region formation. Following this, a vector field approach is employed to split regions comprising of strong edges. Subsequently, all spatially independent...
This study is a comparison between two image segmentation's methods; the first method is based on normal brain's tissue recognition then tumor extraction using thresholding method. The second method is classification based on EM segmentation which is used for both brain recognition and tumor extraction. The goal of these methods is to detect, segment, extract, classify and measure properties of the...
In this paper, we present a new method for removing texture in images using a smoothing rotating filter. From this filter, a bank of smoothed images provides pixel signals able to classify a pixel as a texture pixel, a homogenous region pixel or an edge pixel. Then, we introduce a new method for anisotropic diffusion which controls accurately the diffusion near edge and corner points and diffuses...
Cellular automata are simple models of computation which exhibit fascinatingly complex behavior. They have captured the attention of several generations of researchers, leading to an extensive body of work. The emphasis is mainly on topics closer to computer science and mathematics rather than physics, biology or other applications. Many related works were interested in cellular automata capacities...
We consider the problem of semi-supervised segmentation of textured images. Recently, reweighted belief propagation has been introduced as a solution for Bayesian inference with respect to the maximum posterior mode criterion. In this paper, we show how to adapt reweighted belief propagation to the problem of segmentation of textured images. An adaptive parameter estimation technique is also provided...
This paper proposes a system to relate objects in an image using occlusion cues and arrange them according to depth. The system does not rely on any a priori knowledge of the scene structure and focuses on detecting specific points, such as T-junctions, to infer the depth relationships between objects in the scene. The system makes extensive use of the Binary Partition Tree (BPT) as the segmentation...
The Hierarchical SEGmentation (HSEG) algorithm, which is a combination of hierarchical step-wise optimization and spectral clustering, has given good performances for hyperspectral image analysis. This technique produces at its output a hierarchical set of image segmentations. The automated selection of a single segmentation level is often necessary. We propose and investigate the use of automatically...
Image analysis is still considered as the bottleneck in 2D-gel based expression proteomics analysis for biomarkers discovery. We are presenting a new end-to-end image analysis pipeline of operations that can be fully automated. The pipeline includes image denoising and enhancement based on contourlets, image segmentation into Regions of Interest (ROIs) based on active contours, followed by the analysis...
The aim of this paper is to provide an algorithm for image fusion which combines the techniques of Chebyshev polynomial (CP) approximation and independent component analysis (ICA), based on the regional information of input images. We present a region-based method that combines the merits of both techniques. It utilises segmentation to identify edges, texture and other important features in the input...
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