Literature DB >> 18255381

Automatic text detection and tracking in digital video.

H Li1, D Doermann, O Kia.   

Abstract

Text that appears in a scene or is graphically added to video can provide an important supplemental source of index information as well as clues for decoding the video's structure and for classification. In this work, we present algorithms for detecting and tracking text in digital video. Our system implements a scale-space feature extractor that feeds an artificial neural processor to detect text blocks. Our text tracking scheme consists of two modules: a sum of squared difference (SSD)-based module to find the initial position and a contour-based module to refine the position. Experiments conducted with a variety of video sources show that our scheme can detect and track text robustly.

Entities:  

Year:  2000        PMID: 18255381     DOI: 10.1109/83.817607

Source DB:  PubMed          Journal:  IEEE Trans Image Process        ISSN: 1057-7149            Impact factor:   10.856


  4 in total

1.  Localizing Blurry and Low-Resolution Text in Natural Images.

Authors:  Pannag Sanketi; Huiying Shen; James M Coughlan
Journal:  Proc IEEE Workshop Appl Comput Vis       Date:  2011-02-10

2.  A new pivoting and iterative text detection algorithm for biomedical images.

Authors:  Songhua Xu; Michael Krauthammer
Journal:  J Biomed Inform       Date:  2010-09-29       Impact factor: 6.317

3.  Figure-Ground Segmentation Using Factor Graphs.

Authors:  Huiying Shen; James Coughlan; Volodymyr Ivanchenko
Journal:  Image Vis Comput       Date:  2009-06-04       Impact factor: 2.818

4.  Rotation-invariant features for multi-oriented text detection in natural images.

Authors:  Cong Yao; Xin Zhang; Xiang Bai; Wenyu Liu; Yi Ma; Zhuowen Tu
Journal:  PLoS One       Date:  2013-08-05       Impact factor: 3.240

  4 in total

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