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An improved image segmentation algorithm based on support vector machines was proposed, which belonged to hybrid segmentation techniques. Considering image segmentation based on support vector machines required the user to provide the training data, an automatic data providing method was proposed to obtain training data used by support vector machines instead of directly taking some pieces of the...
Road detection from satellite images can be considered as a classification process in which pixels are divided into road and background classes and can be used as a criterion in road extraction process to discriminate between road and non road pixels. Apart from the spectral information, textural parameters and contextual information are usually used by human being in object recognition from images...
Considering the simplicity and fast training speed of Haar-like features, the high detecting precision of HOG features, a combined method is proposed on the basis of the two features. Several rectangular features which can describe local human characteristics based on original features are added. The combined method can retain the precision of HOG features and increase the speed of detection at the...
This paper introduces a tuning algorithm of self-quotient ε-filter (SQEF) and support vector machine (SVM), and its application to noise robust human detection combining SQEF, histograms of oriented gradients (HOG), and SVM. Although human detection combining HOG and SVM is a powerful approach, as it uses local intensity gradients, it is difficult to handle noise corrupted images. On the other hand,...
In this work, a novel occlusion detection algorithm using online learning is proposed for video applications. Each frame of a video is considered as a time-step for which pixels are classified as being either occluded or non-occluded. The Hedge algorithm is employed to determine weights for a set of experts, each of which is tuned to detect a specific type of occlusion boundary. In contrast to previous...
Video fire detection system which uses a spatio-temporal covariance matrix of video data is proposed. This system divides the video into spatio-temporal blocks and computes covariance features extracted from these blocks to detect fire. Feature vectors taking advantage of both the spatial and the temporal characteristics of flame colored regions are classified using an SVM classifier which is trained...
Detecting stationary human targets is crucial in ensuring safe operation of unmanned ground vehicles. In this paper, a multi-stage detection algorithm for stationary humans in infrared imagery is proposed. This algorithm first applies an efficient feature-based anomalies detection algorithm to search the entire input image, which is followed by an eigen-neural-based clutter rejecter that examines...
In this paper, we present an efficient side information extrapolation scheme with temporal and spatial consistency for low-delay Wyner-Ziv video coding. Our method is based on the regularized local linear regression (RLLR) model, in which each pixel in SI is approximated as a linear weighted combination of samples within a local temporal neighborhood. The optimal model parameters are estimated by...
Computer vision is a growing field of computer science that intends to extract some useful information from images, usually taken from cameras or scanners. The ability to recognize shapes in images is often necessary in computer vision programs. This article describes how to make a program able to recognize basic geometrical figures by using machine learning. This article shows the image processing...
Astronomy provides important challenges for computer sciences, since there are many astronomical phenomena that must be studied through computational means. One of them is cataclysmic variable stars (CV). These phenomena must be studied through indirect observation techniques, since modern instruments are not able to directly obtain information about their structure and behavior. One of such techniques,...
This paper describes the detection of rust defects on highway steel bridges, which are one of the most commonly observed defects on coating surfaces and thus have to be taken care of appropriately since they severely affect the structural integrity of bridges. A rust defect assessment method is presented that automatically detects the percentage of rust in a given digital image of bridge surface taken...
We present a novel method to model and estimate elastic geometric deformations of an observed object, whether they are caused by the object's own dynamic behavior, or by the dynamic behavior of the imaging device, or both. A procedure for estimating the space of possible deformations the object may undergo based only on a set of observations is derived. This information is then employed to derive...
In this paper, a novel intra prediction algorithm, named enhanced line-based intra prediction (ELIP), is proposed to improve the traditional intra prediction methods for image/intra-frame coding. Different from the existing schemes where the interpolation filtering only depends on the intra prediction mode, in the proposed ELIP, the linear filtering coefficients are further refined by imposing both...
Block-based image steganalysis, which uses smaller homogenous blocks from a given test image, was previously proposed to improve the steganalysis performance. Performance study on block-based image steganalysis in terms of block sizes and block numbers is conducted in this research. First, we analyze the dependence of the steganalysis performance on one of these two factors, and show that a larger...
Recently, several papers have proposed pseudo dynamic methods for automatic handwritten signature verification. Each of these papers uses texture measures of the gray level signature strokes. This paper explores the usefulness of local binary pattern (LBP) and local directional pattern (LDP) texture measures to discriminate off-line signatures. A comparison between several texture normalizations is...
A robust automatic crack detection method for nonuniform colour distributions on texture images is proposed. In this method a new image segmentation technique is developed while the Hough transform is used for feature extraction. Meanwhile, the detection is based on standard discriminant analysis, featuring Wilk's λ selection criteria. The methods and procedures were tested on commercial biscuit crackers,...
The launch of last-generation satellites (COSMO-SkyMed and TerraSAR-X), equipped with X-band sensors acquiring images with a very high spatial resolution, has opened up new challenges in the field of SAR image processing for remote sensing applications. In this work, a set of Spotlight and Stripmap COSMO-Skymed images taken the Tor Vergata-Frascati test site was considered to investigate on the potential...
In remote sensing image classification, it is commonly assumed that the distribution of the classes is stable over the entire image. This way, training pixels labeled by photointerpretation are assumed to be representative of the whole image. However, differences in distribution of the classes throughout the image make this assumption weak and a model built on a single area may be suboptimal when...
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