Serwis Infona wykorzystuje pliki cookies (ciasteczka). Są to wartości tekstowe, zapamiętywane przez przeglądarkę na urządzeniu użytkownika. Nasz serwis ma dostęp do tych wartości oraz wykorzystuje je do zapamiętania danych dotyczących użytkownika, takich jak np. ustawienia (typu widok ekranu, wybór języka interfejsu), zapamiętanie zalogowania. Korzystanie z serwisu Infona oznacza zgodę na zapis informacji i ich wykorzystanie dla celów korzytania z serwisu. Więcej informacji można znaleźć w Polityce prywatności oraz Regulaminie serwisu. Zamknięcie tego okienka potwierdza zapoznanie się z informacją o plikach cookies, akceptację polityki prywatności i regulaminu oraz sposobu wykorzystywania plików cookies w serwisie. Możesz zmienić ustawienia obsługi cookies w swojej przeglądarce.
Use of the graph theory tools in image processing field is growing up with each passing day. Graph theory makes the operations easier for image processing applications, and can represent digital image components completely. In image segmentation processes, the graph theory tools are also used widely. These kinds of image segmentation processes are called graph-based image segmentation. In many image...
Image segmentation is a fundamental problem in image processing and computer vision. Its goal is to separate an image into a collection of distinct regions, after which other high-level tasks can be performed. Nomalized cut (Ncut) algorithm is the most popular one in image segmentation algorithms. However, the number of segmentation regions needs to be specified by users or experts before the Ncut...
Segmentation task plays an important role in image processing. In this paper, we attempt to extract information from images using texture analysis. Moreover, we propose characterization of pixels in images to define the similarity relation between them. These are based on textural information and findings of shortest paths in the graph representation of images. To reflect effectiveness of our method,...
Brain connectivity is increasingly being studied using connectomes. Typical structural connectome definitions do not directly take white matter pathology into account. Presumably, pathology impedes signal transmission along fibres, leading to a reduction in function. In order to directly study disconnection and localize pathology within the connectome, we present the disconnectome, which only considers...
Segmentation of specific objects in an image is a key task in computer vision, for which various algorithms have been proposed. However, most of these algorithms are software-oriented and have high computational complexity that makes them difficult to implement in hardware for real-time applications. The semi-supervised graph-based random walker (RW) algorithm, which seeks the solution for a large...
In this paper, we propose a graph affinity learning method for a recently proposed graph-based salient object detection method, namely Extended Quantum Cuts (EQCut). We exploit the fact that the output of EQCut is differentiable with respect to graph affinities, in order to optimize linear combination coefficients and parameters of several differentiable affinity functions by applying error backpropagation...
Image segmentation is one of the most important tasks in Image Analysis since it allows locating the relevant regions of the images and discarding irrelevant information. Any mistake during this phase may cause serious problems to the subsequent methods of the image-based systems. The segmentation process is usually very complex since most of the images present some kind of noise. In this work, two...
Spectral graph theory can characterize the global properties and extract structural information of a graph. The normalized Laplacian matrix of a graph has positive or zero eigenvalues, and the largest eigenvalues is less than or equal to 2. In this paper, the internal rules of the eigenvalues of the normalized Laplacian matrix will be proposed. The range of the eigenvalues is further narrowed and...
Biomedical image processing that offers computer-aided diagnosis is much more popular due to the availability of high quality and large quantity of medical data. Our well-developed biomedical image computing system, which automatically extracts and segments the nucleus and cytoplasm of cell in medical images, is no doubt following this idea. Nonetheless, even though previous system provide good algorithmic...
In this paper, we propose an unsupervised bottom-up method which formulates salient object detection problem as finding salient vertices of a graph. Global contrast is extracted in a novel graph-based framework to determine localization of salient objects. Saliency values are assigned to regions in terms of nodes degrees on graph. The proposed method has been applied on SED2 dataset. The qualitative...
Automatic landmark identification is one of the hot research topics in computer vision domain. Efficient and robust identification of landmark points is a challenging task, especially in a mobile context. This paper addresses the pruning of near-duplicate images for creating representative training image sets to minimize overall query processing complexity and time. We prune different perspectives...
Recently, there has been a lot of work on extending traditional signal processing methods to irregular domains such as graphs. Graph wavelet transform offers a multiscale analysis of graphs similar to traditional wavelets. Similar to wavelets which are effective at detecting transients in a signal, graph wavelets can be used to detect discontinuities of functions defined on graphs. In this paper,...
Unconstrained and contact-free hand recognition problem with mobile devices is not solved yet because these systems have to deal with hard problems like different backgrounds and illumination. Algorithms to perform an image segmentation in order to create regions in the image with the same semantic meaning are a work in progress. Graph theory has been used successfully in order to reach a good image...
Textile image segmentation is widely used in textile industry design, since users often need to reconstruct and redesign the patterns of the textile image. Different from traditional image segmentation methods, this paper focused on handling textile images, which received little attention until now. Taking into account the characteristics of textile, this paper proposed a novel graph theory and region...
Seed-based image segmentation methods have gained much attention lately, mainly due to their good performance in segmenting complex images with little user interaction. Such popularity leveraged the development of many new variations of seed-based image segmentation techniques, which vary greatly regarding mathematical formulation and complexity. Most existing methods in fact rely on complex mathematical...
Two of the biggest challenges in analyzing HyperSpectral Image (HSI) data are that, first, the data is very high-dimensional, and secondly, by its very nature, HSI contains both spatial and spectral information. In order to make full use of this information, models and algorithms should incorporate both aspects of the data; unfortunately, this is a decidedly non-trivial problem. In recent years, spectral...
Image segmentation is a fundamental process in computer vision applications. This paper presents a novel method to deal with the issue of image segmentation. Each image is first segmented coarsely, and represented as a graph model. Then, a semi-supervised algorithm is utilized to estimate the relevance between labeled nodes and unlabeled nodes to construct a relevance matrix. Finally, a normalized...
Image segmentation is the first step in computer vision project. But it is also the key procedure from image processing to image analysis. With the continuous development of computer hardware and technology advances, more attention has been paid to the color image. Based on previous image segmentation technology, this paper proposes a novel color image segmentation method. The method improves the...
Segmentation of anatomical and pathological structures in bladder wall images is crucial for diagnosis and study of bladder diseases. Manual segmentation, which is commonly used in this field, is often a time-consuming and subjective process. Those methods that have proposed normally are not suitable for bladder wall SDOCT (Spectral Domain Optical Coherence Tomography) images, although they do have...
We propose a new graph-based approach for performing a multilabel, interactive image segmentation using the principle of random walks. Using the random walk principle, given a set of user-defined (or prelabeled) pixels as labels, one can analytically calculate the probability of walking from each unlabeled pixel to each labeled pixel, thereby defining a vector of probabilities for each unlabeled pixel...
Podaj zakres dat dla filtrowania wyświetlonych wyników. Możesz podać datę początkową, końcową lub obie daty. Daty możesz wpisać ręcznie lub wybrać za pomocą kalendarza.