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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 paper we present a novel method for automatic text-line parameter selection for stereo image pairs. The parameters are selected such that correspondence between the same content in a stereo pair is maximized. Automatic parameter selection has been carried out by establishing robust text-line correspondence which is also a contribution of the presented work. The proposed method is applied to...
Large-scale digitisation of historical documents demands robust methods that cope with the presence of frequent distortions and noisy artefacts. This paper presents a hybrid text line segmentation method that uses a novel data structure and a rule base to combine the strengths of top-down and bottom-up approaches while minimising their weaknesses. The effectiveness of the proposed approach has been...
An automatic text recognizer needs, in first place, to localize the text in the image the more accurately possible. For this purpose, we present in this paper a robust method for text detection. It is composed of three main stages: a segmentation stage to find character candidates, a connected component analysis based on fast-to-compute but robust features to accept characters and discard non-text...
Center-surround measurements are widely used for saliency detection but with some disadvantages: 1) Center-surround operation may cause inaccurate segmentation and even involve incorrect detection results; 2) In most situations, only using center-surround feature is not efficient to encode object saliency. To overcome these disadvantages, we describe a novel measurement, namely Corner-Surround Contrast...
We propose a two phase line segmentation method for handwritten pre-modern densely written manuscripts. The proposed method combines the robustness of projection based methods with the flexibility of graph based methods. The result are cut-outs of the image containing each text line. Overlapping characters, help lines and degradation can create foreground elements spanning several lines that are hard...
In the paper, we present an approach to efficiently summarizing UAV video data. Our approach is based on first detecting and tracking moving objects. Significant camera motion usually present in UAV video data is successfully handled by a robust feature-based frame registration technique. We then devise a saliency-based scoring method to score and rank detected object tracks. Object tracks are then...
Recently, various approaches to facial expression recognition have been proposed, but they do not provide a powerful approach to recognize expressions from Partially Occluded Facial Images. Moreover, they usually are global and the importance of different areas in facial images is considered equally. In this paper, we propose a novel facial expression recognition approach based on locally weighted...
In this paper, a novel edge-based stereo matching technique is presented. Depth discontinuities are specifically accounted for in the choice of support regions. We employ dynamic programming along edge-segments to efficiently enforce inter-scanline consistency. Although not performing a global optimization over the whole image we show that our approach performs successfully on the Middlebury benchmark...
Diffusion Weighted MR Imaging (DWI) is routinely used for early detection of cerebral ischemic stroke. DWI with higher b-values (b=2000) provide improved sensitivity, higher conspicuity and reduced artifacts and thus improve the detectability of smallest infarcts than conventional DWI (b=1000). We propose a novel framework for accurately detecting stroke regions by combining information from multiple...
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