49,604 research outputs found

    Text Localization in Video Using Multiscale Weber's Local Descriptor

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    In this paper, we propose a novel approach for detecting the text present in videos and scene images based on the Multiscale Weber's Local Descriptor (MWLD). Given an input video, the shots are identified and the key frames are extracted based on their spatio-temporal relationship. From each key frame, we detect the local region information using WLD with different radius and neighborhood relationship of pixel values and hence obtained intensity enhanced key frames at multiple scales. These multiscale WLD key frames are merged together and then the horizontal gradients are computed using morphological operations. The obtained results are then binarized and the false positives are eliminated based on geometrical properties. Finally, we employ connected component analysis and morphological dilation operation to determine the text regions that aids in text localization. The experimental results obtained on publicly available standard Hua, Horizontal-1 and Horizontal-2 video dataset illustrate that the proposed method can accurately detect and localize texts of various sizes, fonts and colors in videos.Comment: IEEE SPICES, 201

    A user evaluation of hierarchical phrase browsing

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    Phrase browsing interfaces based on hierarchies of phrases extracted automatically from document collections offer a useful compromise between automatic full-text searching and manually-created subject indexes. The literature contains descriptions of such systems that many find compelling and persuasive. However, evaluation studies have either been anecdotal, or focused on objective measures of the quality of automatically-extracted index terms, or restricted to questions of computational efficiency and feasibility. This paper reports on an empirical, controlled user study that compares hierarchical phrase browsing with full-text searching over a range of information seeking tasks. Users found the results located via phrase browsing to be relevant and useful but preferred keyword searching for certain types of queries. Users experiences were marred by interface details, including inconsistencies between the phrase browser and the surrounding digital library interface

    NASA gateway requirements analysis

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    NASA devotes approximately 40 percent of its budget to R&D. Twelve NASA Research Centers and their contractors conduct this R&D, which ranges across many disciplines and is fueled by information about previous endeavors. Locating the right information is crucial. While NASA researchers use peer contacts as their primary source of scientific and technical information (STI), on-line bibliographic data bases - both Government-owned and commercial - are also frequently consulted. Once identified, the STI must be delivered in a usable format. This report assesses the appropriateness of developing an intelligent gateway interface for the NASA R&D community as a means of obtaining improved access to relevant STI resources outside of NASA's Remote Console (RECON) on-line bibliographic database. A study was conducted to determine (1) the information requirements of the R&D community, (2) the information sources to meet those requirements, and (3) ways of facilitating access to those information sources. Findings indicate that NASA researchers need more comprehensive STI coverage of disciplines not now represented in the RECON database. This augmented subject coverage should preferably be provided by both domestic and foreign STI sources. It was also found that NASA researchers frequently request rapid delivery of STI, in its original format. Finally, it was found that researchers need a better system for alerting them to recent developments in their areas of interest. A gateway that provides access to domestic and international information sources can also solve several shortcomings in the present STI delivery system. NASA should further test the practicality of a gateway as a mechanism for improved STI access

    Colour Text Segmentation in Web Images Based on Human Perception

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    There is a significant need to extract and analyse the text in images on Web documents, for effective indexing, semantic analysis and even presentation by non-visual means (e.g., audio). This paper argues that the challenging segmentation stage for such images benefits from a human perspective of colour perception in preference to RGB colour space analysis. The proposed approach enables the segmentation of text in complex situations such as in the presence of varying colour and texture (characters and background). More precisely, characters are segmented as distinct regions with separate chromaticity and/or lightness by performing a layer decomposition of the image. The method described here is a result of the authors’ systematic approach to approximate the human colour perception characteristics for the identification of character regions. In this instance, the image is decomposed by performing histogram analysis of Hue and Lightness in the HLS colour space and merging using information on human discrimination of wavelength and luminance
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