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.
We aim to match two hypergraphs via pairwise characterization of multiple relationships. To this end, we introduce a technique referred to as Marginalized Constrained Compatibility Estimation (MCCE), which transforms the compatibility tensor representing hyper-edge similarities into a compatibility matrix representing edge similarities. We then cluster graph vertices associated with the compatibility...
Detection of vortices, which are rotating flow features, is an important task to identify, analyze, and understand flow dynamics in a fluid. For example, it can be used to accurately tag nonrigid salient rotation features from large amount of wind vectors captured by orbiting satellites for hurricane research. In this paper, we describe in detail a general vortex detection algorithm motivated by Hough...
In order to achieve high accuracy of face recognition, detection of facial parts such as eyes, nose, and mouth is essentially important. In this paper, we propose a method to detect eyes from frontal face images. The proposed method consists of two major steps. The first is two dimensional Hough transformation for detecting circle of unknown radius. The circular Hough transform first generates two...
We present an ensemble recognition method for graphic symbols that could be interfered by intersecting objects from the context. The symbol is first represented as a set of shape points, each of which is described by a shape context pyramid capturing the local shape characteristics of multi-scale regions surrounding the shape point. A Hough forest ensemble classifier is then employed to learn the...
Imaging neural stem cells/ neurospheres using low magnification brightfield modality results in uneven illumination effects across the field of view. Globally, the centre appears bright while the edges appear dark; locally, illumination varies across individual adjacent site images. Furthermore, neurospheres residing in the dark background regions have low signal:noise ratio. Altogether, they impose...
In this paper, based on a novel integer transform, an efficient reversible image watermarking method is proposed. The integer transform is a generalization of some previous works. It can be applied to a pixel block of arbitrary size with adjustable capacities. Moreover, this transform is conducted by conditionally embedding data only when the estimated distortion is acceptable. By this approach, our...
Repeated appearance of any block of spatial data in document images can be cached and encoded single time to get good compression ratio. This Reusable Document Component (RDC) can replicate the blocks of each redundant image at the receiver side at different positions but with same size and orientation. We have proposed a novel algorithm of Orientation Scale mapped RDC (OS-RDC) which can identify...
Symbol retrieval for technical documents is still a hot challenge in the document analysis community. In this paper we propose another way to spot symbols. A pixel-based template operator which is an adaptation of the hit-or-miss transform is defined. This operator is robust to translation, rotation and reflection. Experimental results on a real application show the efficiency of our approach.
In this paper, we present a new method for text extraction in real scene images. We propose first a skeleton based descriptor to describe the strokes of the text candidates that compose a spatial relation graph. We then apply the graph cuts algorithm to label the nodes of the graph as text or non-text. We finally refine the resulted text lines candidates by classifying them using a kernel SVM. To...
In this article, we present a novel set of features for detection of text in images of natural scenes using a multi-layer perceptron (MLP) classifier. An estimate of the uniformity in stroke thickness is one of our features and we obtain the same using only a subset of the distance transform values of the concerned region. Estimation of the uniformity in stroke thickness on the basis of sparse sampling...
Seeded segmentation methods attempt to solve the segmentation problem in the presence of prior knowledge in the form of a partial segmentation, where a small subset of the image elements (seed-points) have been assigned correct segmentation labels. Common for most of the leading methods in this area is that they seek to find a segmentation where the boundaries of the segmented regions coincide with...
Unmanned Aerial Vehicles (UAV) become widely used as they present many advantages for surveillance applications. However, most computer vision algorithms cannot be applied to the video sequences from UAV due to video shaking or blurredness. We propose a method to stabilize the image sequence from UAV cameras. This approach deals with three steps, a keypoint detection step, then a homography estimation...
Sharing of hyper-parameters is often useful for multi-task problems as a means of encoding some notion of task similarity. Here we present a multi-task approach for signal recovery by sharing higher-level hyper-parameters which do not relate directly to the actual content of the signals of interest but only to their statistical characteristics. Our approach leads to a very simple model and algorithm...
In this paper, a novel histogram-based model for contrast enhancement is proposed. Based on our analysis about the relationships of histogram with contrast, we establish a model which 1) achieves contrast enhancement by an optimal transform of histogram, 2) gives two metrics called contrast gain and nonlinear-ity of transform to measure the strength of enhancement and the seriousness of distortion...
To efficiently detect all the possible linear features, a multi scale multi structuring element top-hat transform based algorithm is proposed in this paper. The algorithm is divided into two parts: the multi scale multi structuring element top-hat transform and postprocessing. In the multi scale multi structuring element top-hat transform, multi scales of multi structuring elements with increasing...
In this paper we propose a novel method of estimating vanishing point by spherical gradient. In contrast with the conventional methods in which vanishing point is estimated from lines, the proposed method does not necessarily extract lines, but employs the spherical gradient cues of edge points. Based on the observation that spherical gradient is aligned with the normal vector of the projection plane...
In this paper, we propose a novel text detection approach based on stroke width. Firstly, a unique contrast-enhanced Maximally Stable Extremal Region(MSER) algorithm is designed to extract character candidates. Secondly, simple geometric constrains are applied to remove non-text regions. Then by integrating stroke width generated from skeletons of those candidates, we reject remained false positives...
This paper presents a new discriminative linear regression approach to adaptation of a discriminatively trained prototype-based classifier for Chinese OCR. A so-called sample separation margin based minimum classification error criterion is used in both classifier training and adaptation, while an Rprop algorithm is used for optimizing the objective function. Formulations for both model-space and...
Semi-supervised classification from pairwise constraints is a challenge in pattern recognition, since the constraints just represent the relationships between data pairs rather than the definite labels. In the last few years, several methods have been proposed, however, they still utilize either the discriminability within the constraints or the abundant unlabeled data insufficiently. In this paper,...
Night Removal is highly desired in both computational photography and computer vision applications. However, few works have been studied towards this goal. This paper proposes an effective algorithm for removing the night from a single input image. We present a new Color Estimation Model (CEM) for transforming the image from “night” to “day” — along with a guided statistical Dark-to-Day (D2D) prior...
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.