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.
Since edge indicates the outline of an object and also can provides important information to separate the objects from the background or other overlapping objects, edge detection is an essential tool in image processing and computer vision. Compared with gray image, color image provides more edge information of objects. However, the current color edge detection algorithms acquired so much time to...
Based on the good performances of nonlinear diffusion in preserving important image features, the Curvature-driven with Edge-stopping(C&E model) is proposed and applied into image zooming. The C&E model can protect little curvature and emphasize big gradient; at same time, it has two effects of connecting broken level sets and strengthening edges. Its performance was further evaluated by the...
In this paper, we propose an unsupervised segmentation algorithm for extracting moving objects/regions from compressed video using Markov Random Field (MRF) classification. First, motion vectors (MVs) are quantized into several representative classes, from which MRF priors are estimated. Then, a coarse segmentation map of the MV field is obtained using a maximum a posteriori estimate of the MRF label...
Traffic flow, analysis and control is gaining high relevance, as the number of circulating vehicles continuously increases. This article proposes a computer vision based platform, which automatically detects vehicles in order to infer the traffic conditions. The developed real time detection algorithm is based on a dual background subtraction technique, incorporating the one known has Codebook and...
Image segmentation is an important and difficult task in computer vision applications. Various methods have been introduced in the past to use gray-level histogram in deciding the segmentation threshold for monochrome images. With the reducing price of color cameras, different color spaces have also been considered in color image based segmentations. In this paper, a study of the effect of color spaces...
We propose a method for the detection of high frequency regions using multiresolution analysis and orientation tensors. A scalar field representing multiresolution edges is obtained. Local maxima of this scalar space indicate regions having coincident detail vectors in multiple scales of a wavelet decomposition. This is useful for finding edges, textures, collinear structures and salient regions for...
An edge in an image is the boundary between two different regions. Edge detection is important in image processing and computer vision, particularly in the area of feature detection. An edge often indicates the physical extent of object within the image. An edge detection process ultimately aims to obtain a binary edge map. In this paper, we propose a new scheme for edge detection. It is simple but...
Edge detection is one of the most commonly used operations in image processing and pattern recognition, the reason for this is that edges form the outline of an object. An edge is the boundary between an object and the background, and indicates the boundary between overlapping objects. This means that if the edges in an image can be identified accurately, all of the objects can be located and basic...
Edge detection is one of the most commonly used operations in image processing and pattern recognition, the reason for this is that edges form the outline of an object. An edge is the boundary between an object and the background, and indicates the boundary between overlapping objects. This means that if the edges in an image can be identified accurately, all of the objects can be located and basic...
The intrinsic image composed of reflectance and shading images plays important roles in various computer vision applications. This paper focuses on solving the problem of intrinsic image decomposition. Based on the assumption that the image derivatives can be classified into either reflectance-related or shading-related, the reflectance and shading image can be restored from the classified derivatives...
Image segmentation is a fundamental task in many computer vision applications. In this paper, we propose a new unsupervised color image segmentation algorithm, which exploits the information obtained from detecting edges in color images in the CIE L*a*b* color space. To this effect, by using a color gradient detection technique, pixels without edges are clustered and labeled individually to identify...
Curve detection is one of the fundamental steps in computer vision applications. Conventional edge detectors provide only an output of edge pixels; curve matching is then needed to fit edge pixels into curves. Despite having achieved some success, it suffers constraints for applications that require real-time and robust image analysis, such as robot vision and video surveillance. Gao and Wang [11]...
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.