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This paper presents an algorithm for localization and classification of subtitles in TV videos. We extend an existing static-region detector with object-based adaptive temporal filtering, bounding box computation around blobs of refined static regions, bounding box categorization based on geometry and filling degree of static regions, and subtitle classification using text-stroke alignment features...
This paper presents a system for the optimization of text recognition algorithms. First a theoretic four-staged model of text recognition is proposed. In this four-staged model, the second stage called text localization is optimized. A reinterpreted version of the F measure is used as a fitness indicator for optimization of the localization. The optimization method is described and the role of the...
Automatic categorization of videos in a Web-scale unconstrained collection such as YouTube is a challenging task. A key issue is how to build an effective training set in the presence of missing, sparse or noisy labels. We propose to achieve this by first manually creating a small labeled set and then extending it using additional sources such as related videos, searched videos, and text-based webpages...
The detection of texts in video images is an important task towards automatic content-based information indexing and retrieval system. In this paper, we propose a texture-based method for text detection in complex video images. Taking advantage of the desirable characteristic of gray-scale invariance of local binary patterns (LBP), we apply a modified LBP operator to extract feature of texts. A polynomial...
A novel method is proposed in this paper to detect texts from scene images captured by digital cameras. It converts the text detection problem to a shape classification problem by means of the topographic maps, and performs shape classification by exploiting the over-complete and sparse structure in the shape data. Finally, layout analysis is applied to complete the text line detection. The proposed...
Text in images and videos is a significant cue for visual content understanding and retrieval. In this paper, we present a fast and effective approach to locate text lines even under complex background. First, our algorithm uses the stroke filter to calculate the stroke maps in horizontal, vertical, left-diagonal, right-diagonal directions. Then a 24- dimensional feature is extracted for each sliding...
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