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Detecting text in natural scenes with stroke width transform

Detecting text in natural scenes with stroke width transform,10.1109/CVPR.2010.5540041,Boris Epshtein,Eyal Ofek,Yonatan Wexler

Detecting text in natural scenes with stroke width transform   (Citations: 8)
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We present a novel image operator that seeks to find the value of stroke width for each image pixel, and demonstrate its use on the task of text detection in natural images. The suggested operator is local and data dependent, which makes it fast and robust enough to eliminate the need for multi-scale computation or scanning windows. Extensive testing shows that the suggested scheme outperforms the latest published algorithms. Its simplicity allows the algorithm to detect texts in many fonts and languages.
Conference: Computer Vision and Pattern Recognition - CVPR , pp. 2963-2970, 2010
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    • ...Very recently, Epshtein et al. [6] presented a detector based on the “stroke width transform” and showed very promising results on the ICDAR dataset...
    • ...This falls within the middle range of values published in [12], but cannot compete with the best scoring algorithms in [12] and [6], which achieve precision and recall values of 60 ‐ 70%...
    • ...It should again be noted that our algorithm requires a single point as input, while the other algorithms are fully automatic, but also that our algorithm runs in less than 0.5 s on a mobile device and is hence one to two orders of magnitude faster than the aforementioned algorithms (see timings in [6, 12])...
    • ...A promising approach would be to integrate the recent work by Epshtein et al. [6] and to try to decrease the runtime requirements by, for example, leveraging the seed point provided by the user...

    Victor Fragosoet al. TranslatAR: A mobile augmented reality translator

    • ...The most challenging sub-problem in this system is the text detection and character recognition itself (a problem that has warranted much prior work [6], [7], [8], [9], [10])...

    Carl Caseet al. Autonomous sign reading for semantic mapping

    • ...Recent work on text localization [3], which outperforms the latest published algorithms, estimates the local width of stroke features in the image, and identifies text regions on the basis of local homogeneity of this stroke width (corresponding to consistent stroke widths in characters)...

    Pannag Sanketiet al. Localizing blurry and low-resolution text in natural images

    • ...However, since some of the input images might be taken in different light conditions or different angle, the best approach to detect this text was by applying Epsteins’ Stroke Width Transform (SWT) algorithm [1]...

    V. Shehuet al. Object class recognition using range of multiple computer vision algor...

    • ...[1]‐[4]). The challenges with wild text include the lack of contrast between text and its background, the rich diversity of fonts and character sizes, highly variable horizontal and vertical alignment of characters and related words, and perspective distortion due to non fronto-parallel viewing...
    • ...[1]‐[4]). ICDAR 1 has organised two competitions (2003 and 2005) for the robust detection of wild text based on a standard set of labelled images...

    Ingmar Posneret al. Using text-spotting to query the world

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