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The following topics are dealt with: computer vision; pattern recognition; image, speech, and signal processing; multimedia and video analysis; document analysis and biometrics.
This paper introduces a clever way of computing inner products between images in order to drastically reduce the computational complexity of fitting appearance models to images. This speedup is possible since computing the hessian matrix for the parameter updates becomes several orders of magnitude faster which in turn has enormous impact on applications. Contrary to previous work within the area,...
In this article, we present the projective equation of a circle in a perspective view, which naturally encodes such important geometric entities as the projected circle center, the vanishing point of the normal direction of the circlepsilas supporting plane and the degenerate conic envelope spanned by the image of circular points (ICPs). Based on this projective equation, we propose an easy technique...
In this paper, a novel approach to mathematical morphology operations is proposed. Morphological operators based on partial differential equations (PDEs) are extended to weighted graphs of the arbitrary topologies by considering partial difference equations. We focus on a general class of morphological filters, the levelings; and propose a novel approach of such filters. Indeed, our methodology recovers...
Image analysis tools that process the image using polar coordinates are needed to avoid the interpolation from polar to cartesian coordinates. We present a tool for analysing and processing circular objects - the polar distance transform computed by fast-marching. The fast marching method can be used for computing the grey-weighted distance transform by numerically approximating the Eikonal differential...
We propose an algorithm that equalizes the contrast of grayscale image pairs to simplify the task of change detection. To ensure robustness of the detection under different illumination conditions, some authors recently proposed algorithms that compare the level lines of the images. We show - using ideas from the ldquoshape from shadingrdquo community - that under directed light, a necessary condition...
In this paper, an entropic thresholding method based on the gray-level spatial correlation (GLSC) histogram defined by ourselves is presented. Compared with traditional two-dimensional histogram, we take into account the image local property in a different way by GLSC histogram. In experiment, we make comparison of the proposed method with two-dimensional entropic thresholding method proposed by Abutaleb...
Many on-line photo sharing systems allow users to tag their images so as to support semantic image search. In this paper, we study how one can take advantages of the already-tagged images to (semi-)automate the labeling of newly uploaded ones. In particular, we propose a hybrid approach for the prediction where user-provided tags and image visual contents are fused under a unified probabilistic framework...
Point-of-interest detection is a way of reducing the amount of data that needs to be processed in a certain application and is widely used in 2D image analysis. In 2D image analysis, point-of-interest detection is usually related to extraction of local descriptors for object recognition, classification, registration or pose estimation. In analysis of range data however, some local descriptors have...
This paper proposes a free-viewpoint imaging method that can be used in a complicated scene such as an office room by using sparsely located cameras. In our method, a free-viewpoint image is generated from multiple image patches obtained by dividing observed images. The quality of the generated image strongly depends on how to divide the observed images. In an incorrect patch in the generated image,...
This paper presents a highly accurate and efficient method for crack detection using percolation-based image processing. The detection of cracks in concrete surfaces during the maintenance and diagnosis of concrete structures is important to ensure the safety of these structures. Recently, the image-based crack detection method has attracted considerable attention due to its low cost and objectivity...
Image quality assessment (IQA) is of great importance for many image processing applications. Some IQA indexes proposed recently more or less try to boost their performance to accord with human subjective evaluation by simulating human visual system (HVS). However, they do not take global salient features into consideration, because of the lack of methods with low computational complexity for simulating...
In this paper, we present a text detection and localization method. Our detection technique is based on a cascade of boosted ensemble and localizer uses standard image processing techniques. We propose a small set of features (39 in total) capable of detecting various type of text in grey level natural scene images. Two weak learners, linear discriminant function and log likelihood-ratio test under...
Biological conclusions reached during microarray experiments can be greatly affected by human intervention, which is currently required in microarray image analysis. Therefore, accurate and automatic analysis of cDNA microarray images becomes crucial. In this paper, an automatic approach to microarray image analysis is presented. The proposed approach is based on the concept of evolution in order...
A very compact algorithm is presented for fitting an ellipse to points in images by maximum likelihood (ML) in the strict sense. Although our algorithm produces the same solution as existing ML-based methods, it is probably the simplest and the smallest of all. By numerical experiments, we show that the strict ML solution practically coincides with the Sampson solution.
Active contours were proposed by Kass et al. as a way to represent the contours of an image. Although the method is simple, one of its shortcomings is its inability to converge into concave structures. The gradient vector flow (GVF) algorithm was put forth by Xu and Prince to succesfully address the concave structure problem. Although there has been much research into GVF, little has been done to...
A lot of image analysis problems lend themselves to a unified mathematical formulation as optimization problems. Tree-serial dynamic programming is a particular case of the so-called nonserial dynamic programming designed for optimization of objective functions which are sums of partial functions each of a smaller number of variables. It is known that these problems are NP-hard in the general formulation,...
We present a distributed machine learning framework based on support vector machines that allows classification problems to be solved iteratively through parallel update algorithms with minimal communication overhead. Decomposing the main problem into multiple relaxed subproblems allows them to be simultaneously solved by individual computing units operating in parallel and having access to only a...
We present the Higher Order Proxy Neighborhoods (HOPS) approach to modeling higher order neighborhoods in Markov Random Fields (MRFs). HOPS incorporates more context information into the energy function in a recursive and cached manner. It induces little or no additional computational cost in the overall minimization process, and can better represent the underlying energy leading to fewer total computations...
This paper addresses the relationship between the visual assessment of cluster tendency (VAT) algorithm and Dunnpsilas cluster validity index. We present an analytical comparison in conjunction with numerical examples to demonstrate that the effectiveness of VAT in showing cluster tendency is directly related to Dunnpsilas index. This analysis is important to understanding the underlying theory of...
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