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The objective measurement of blurring artifacts plays an important role in the dynamic monitoring, adjusting image quality, optimizing algorithms and parameter settings in a variety of image and video processing applications. In this paper, we propose a no-reference metric to estimate blurriness distortion. The work addresses the problem that existing no-reference metrics fail to predict the correct...
The use of vehicles in our life is increasing exponentially day by day and as increasing vehicles are violating the traffic rules, theft of vehicles, entering in restricted areas, high number of accidents lead to increase in the crime rates linearly. For any vehicle to be recognized, vehicle license plate detection will play a major significant role in this active world. For finding vehicles commonly...
Interactive image segmentation is able to extract the user-specified foreground objects from the whole image, which remains to be a challenging problem in image processing and computer vision. The traditional pixel-based interactive segmentation is time-consuming and neglects the neighbor information, which is hard to achieve efficient and accurate results. To address this problem, a novel region-based...
Current medical practice for determining hemoglobin concentration (which is especially important for anemic patients in need of blood transfusion) involves frequent blood tests. In this work, we propose an alternative, non-invasive approach to hemoglobin estimation, based on image analysis of a specific conjunctival region. Our ultimate goal is to develop an easy-to-use wearable device that patients...
The real-time information on the Web changes dynamically and surge quickly, which cause considerable difficulty in access to interested information. How to mine hot events, how to analyze the correlation of events and how to organize information structurally are challenging tasks. In this paper, to address these problems, we propose STeller, an approach to mine context-aware story — a series of correlated...
Medical image processing is used for the diagnosis of diseases by the physicians or radiologists. Noise corrupts medical images and hence qualities of the images are degraded. This degradation includes suppression of edges, structural details, blurring boundaries etc. Therefore image denoising is a very important task and noise should be filtered out, without affecting important features of the image...
Image forgery detection is always a challenging task especially when it comes to the blind image forgery detection techniques which do not contain any water marks or signatures. Copy move forgery is a popular blind image forgery detection technique which is widely used by forgers for performing easy and efficient forgery. A copy-move forgery followed by rotation and scaling of the forged part is even...
Fog is a natural and meteorological phenomenon that seems to be very dangerous for road driving. In its presence, the driver has a high perturbation in his field of view and must redouble vigilance. Therefore, it's primary to detect its presence to be able to adapt any advanced driver assistance system according to the density of fog. In this paper, we present a new local approach for detecting daytime...
Single-sensor multispectral cameras, that sample spectral channels using a multispectral filter array, have recently emerged. They provide a raw image in which each channel is spectrally sampled pixel-wise according to the filter array pattern. A demosaicing procedure is then needed to estimate a multispectral image with full spectral resolution. The usefulness of intensity-based demosaicing has been...
Dense subgraph detection is one of the most important topics in graph analysis. Most previous work on this issue assume an adjacency list or a stream of edges for the target graph. In most real applications however, the underlying graphs only allow navigational access by following links from one node to another. In this paper, we propose a dense subgraph detection technique under the navigational...
The emerging High-Efficiency Video Coding (HEVC) standard has introduced a number of new coding tools, such as a quad-tree based coding unit (CU). The quadtree-structured coding unit achieves significant coding efficiency improvements compared to H264/AVC. However, the complexity of CU depth decision associated with Rate-Distortion (R-D) cost computation dramatically increased. In order to alleviate...
The main emphasis of this paper is to develop an approach able to detect and assess blindly the perceptual blur degradation in images. The idea deals with a statistical modelling of perceptual blur degradation in the frequency domain using the discrete cosine transform (DCT) and the Just Noticeable Blur (JNB) concept. A machine learning system is then trained using the considered statistical features...
It is well know that a measure of contrast in images is not yet fully defined. The conventional measures of contrast consist of global computations and therefore they have a poor performance. At the same time image quality assessment is often based on quantifying the visibility between a structure of interest or foreground and its surrounding background, i.e., the contrast ratio. Then, a high quality...
In this paper a new object-oriented segmentation method for high-resolution remote sensing images is proposed. To limit computational complexity, a preliminary superpixel representation of the image is obtained by means of a suitable watershed transform. Then, a region adjacency graph is associated with the superpixels, with edge weights accounting for region similarity/dissimilarity. The final segmentation...
Soft play is a form of cheating where players deliberately play easy against each other. We evaluate different methods for detecting the players engaging in soft play in shooter games using data generated with synthetic players. These methods are used when analysing the hit matrix of the game.
Traffic density estimation is one of the most challenging problems in Intelligent Transportation Systems. In this paper, we estimate the traffic flow density based on classification. Various new efficient features are introduced for distinguishing between different traffic states, including number of key-points, edges of difference-image and moving edges. These features describe the traffic flow without...
Achieving high accuracy for classifying foreground and background is an interesting challenge in the field of scene image analysis because of the wide range of illumination, complex background, and scale changes. Classifying foreground and background using bag-of-feature model gives a good result. However, the performance of the classifier depends on designed features. Therefore, this paper presents...
In real-world social networks, there is increasing interest in tracking the evolution of groups of users. Existing approaches track evolving communities, in a time-sequential way, by comparing communities in terms of nodes using a similarity measure such as the Jaccard or a modified Jaccard measure. The measure allows the use of a one-to-one comparison in order to match communities. However, tracking...
In the field of ISI-free region detection, few attention was received on the threshold's optimization. In this paper, a sub-optimal analytical solution is introduced for choosing the threshold in high-mobility fading channels based on 1-norm distance, which was suggested to improve the detection accuracy and the computational complexity. Further more, based on the sub-optimal threshold, the 1-norm...
We propose method for fast action recognition and comparable performance using local autocorrelation of optical flows over time. To capture action movement, dense optical flows is generated along sequence of video. Optical flows sometimes yield noise of motions that distract object of interest from another object motions and background. We suppress this by using edge based optical flow. The HOF vector...
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