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Titlebook: Camera-Based Document Analysis and Recognition; 5th International Wo Masakazu Iwamura,Faisal Shafait Conference proceedings 2014 Springer I

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Robust Binarization of Stereo and Monocular Document Images Using Percentile Filter of scanned documents which in general have uniform illumination and high resolution with negligible geometric artifacts. Contrary to this, camera captured images generally are low resolution, contain non-uniform illumination and also posses geometric artifacts. The most important artifact is the de
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Mobile Phone Camera-Based Video Scanning of Paper Documentsd, processing capable and motion sensors equipped smartphones. We present our ongoing research on mobile phone camera-based document image mosaic reconstruction method for video scanning of paper documents. In this work, we have optimized the classic keypoint feature descriptor-based image registrat
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Real-life Activity Recognition – Focus on Recognizing Reading Activitiesacquisition tasks. We are especially interested one particular cognitive task, namely reading (the decoding of letters, words and sentences into information) Reading is a ubiquitous activity that many people even perform in transit, such as while on the bus or while walking. Tracking reading and oth
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The Ups and Downs of Neuropeptides, an environment in which text occurs at a variety of locations, scales and orientations with respect to the observer. Our method uses simultaneous localization and mapping (SLAM) to extract planar “tiles” representing scene surfaces. Multiple observations of each tile, captured from different observ
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C. J. P. Grimmelikhuijzen,F. Hauser characters have different visual properties from their non-character neighbors, which make them salient. With this assumption, characters should response well to computational models of visual saliency. However in some situations, characters belonging to scene text mignt not be as salient as one mi
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Horst-Werner Korf,Klaus-Henning Usadelst identify pixels which are highly specular. Connected components of this set of specular pixels are obtained. Pixels belonging to each such component are separately binarized using the well-known Otsu’s approach. We next apply smoothing on the whole image before obtaining its Canny edge representa
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Neuroendocrine Regulation of Pubertypearance is modeled with an SVM based dictionary classifier and the component consensus is represented with color and spatial layout features. Responses of the dictionary classifier are integrated with the consensus features into a discriminative model, where the importance of features is determined
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