The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
In the complex stomach epidermis tumor cells, the traditional segmentation algorithms such as the K-means clustering algorithm and the simple threshold segmentation algorithm are unable to get satisfactory results. The relaxation iterative segmentation algorithm can segment the cell clearly, but it wastes a lot of time and the execution efficiency is very low. In this paper the authors propose a new...
Dermoscopy is one of the major imaging modalities used in the diagnosis of melanoma and other pigmented skin lesions. Due to the difficulty and subjectivity of human interpretation, automated analysis of dermoscopy images has become an important research area. Border detection is typically the first step in this analysis yet is often limited by the quality of the images to be analyzed. In this paper,...
A discretized parametric curve can be seen as a sparse graph of vectors where each vertex is linked to two other vertices. Following this observation, we propose to generalize parametric active contours to a larger framework we call active vector graphs. This can be achieved by allowing each vertex of a graph of vectors to be linked to more than two vertices. An active graph does not need to be parameterized...
In this paper, the crowd counting and segmentation problem is formulated as a maximum a posterior problem, in which 3D human shape models are designed and matched with image evidence provided by foreground/background separation and probability of boundary. The solution is obtained by considering only the human candidates that are possible to be un-occluded in each iteration, and then applying on them...
Image thresholding is a critical process in digital image processing application. However, there are some disturbing factors like image vagueness and bad illumination resulting in not satisfied image thresholding output. Several fuzzy thresholding techniques are developed to remove graylevel ambiguity during threshold selection. One of the techniques is thresholding method using type II fuzzy sets...
Sparse orthonormal transforms (SOT) has recently been proposed as a data compression method that can achieve sparser representations in transform domain. Given initial conditions, the optimization method utilized to generate the dictionary of SOT also achieves the optimal orthonormal transform for hard thresholding. In the context of translation-invariant denoising, one can use this dictionary to...
A novel approach is proposed to estimate the parameters of a diffeomorphism that aligns two binary images. Classical approaches usually define a cost function based on a similarity metric and then find the solution via optimization. Herein, we trace back the problem to the solution of a system of nonlinear equations which directly provides the parameters of the aligning transformation. The proposed...
H.264 rate control is an interesting problem that has motivated numerous possible solutions. The challenge lies in determining a quantization parameter Qp that will be used for both the rate-distortion (R-D) optimization process and the quantization of transform coefficients. In this work, we attempt to achieve effective rate control with a different approach. By modelling the relationships of distortion,...
AM-FM analysis methods have been used in several biomedical imaging applications. In this paper, we are interested in the development of AM-FM analysis methods for small components, regions of interests (ROIs), and segmented objects. For detecting small components, we propose the use of a new multi-scale AM-FM edge and peak analysis system. The new system uses the product of gradient estimates from...
Many medical image segmentation techniques have been proposed by lots of authors but they are mainly dedicated to particular solutions. There is no generic method for solving the image segmentation problem. The difficulty comes from that two types of noise are presented in medical images: physical noise due to the acquisition system, for example, Optical, X-rays and MRI, and physiological noise due...
The pulse coupled neural network (PCNN) algorithm has been effectively used in image segmentation. In this paper, we proposed a new image auto-segmentation algorithm based on PCNN and fuzzy mutual information (FMI). The image was firstly segmented by PCNN, and then FMI was used as the optimization criterion to automatically stop the segmentation with the optimal result. Different images were segmented...
Medical image registration is a critical step in medical image processing. In this paper, a mixed-type image registration approach is presented, which combines the segmentation-based and voxel-based registration. Firstly, the experimental images are preprocessed, including digital imaging and communication of medicine (DICOM) format conversion, denoising, and segmentation. Then mutual information...
An adaptive Graph-cut algorithm to video moving objects segmentation was proposed. By the Kalman prediction of the number of objectives pixels and objectives-background pixel-pairs, and adaptive updating of the nodes flux, the Graph-cut algorithm was successfully applied to video moving objects segmentation. It was achieve to continuous global optimization segmentation of video moving objects. Experimental...
In this paper, we address the problem of image segmentation using unsupervised clustering method. We implement two nature inspired memetic metaheuristics for segmenting images into regions. First, we use shuffled frog leaping algorithm (SFLA) to locate the optimal clusters for the images. We further use the clonal selection based shuffled frog leaping algorithm (CSSFLA) for segmenting the same images...
Image segmentation is a key technique of image processing and computer vision field. However, facing with large amount of image segmentation methods, the qualitative and quantitative evaluation of algorithms is very significant. This paper states the thoughts of high resolution RS image segmentation methods evaluation and tests it by evaluating four typical image segmentation algorithms based on features...
In this paper we propose a novel iterative algorithm for wavelet-based image denoising following a Maximum a Posteriori (MAP) approach. The wavelet shrinkage problem is modeled according to the Bayesian paradigm, providing a strong and extremely flexible framework for solving general image denoising problems. To approximate the MAP estimator, we propose GSAShrink, a modified version of a known combinatorial...
In the context of image segmentation, Markov random fields (MRF) are extensively used. However solution of MRF-based models is heavily dependent on how successfully the MRF energy minimization is performed. In this framework, two methodologies, complementary to each other, are proposed for random field optimization. We address the special class of models comprising a random field imposed on the probabilities...
Glaucoma is the second leading cause of blindness. Glaucoma can be diagnosed through measurement of neuro-retinal optic cup-to-disc ratio (CDR). Automatic calculation of optic cup boundary is challenging due to the interweavement of blood vessels with the surrounding tissues around the cup. A Convex Hull based Neuro-Retinal Optic Cup Ellipse Optimization algorithm improves the accuracy of the boundary...
Detection of linear structure is a very important problem in image processing and computer vision. The task of finding lines in 2D images has long being studied, but the work in 3D space does not have any promising work yet. This paper investigates the issue of line detection for range images. It proposes an approach to find a wire-frame composed of lines that can represent precisely and comprehensively...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.