Proceedings ArticleDOI
Text localization, enhancement and binarization in multimedia documents
Christian Wolf,J.-M. Jolion,Francoise Chassaing +2 more
- Vol. 2, pp 1037-1040
TLDR
An algorithm to localize artificial text in images and videos using a measure of accumulated gradients and morphological post processing to detect the text is presented and the quality of the localized text is improved by robust multiple frame integration.Abstract:
The systems currently available for content based image and video retrieval work without semantic knowledge, i.e. they use image processing methods to extract low level features of the data. The similarity obtained by these approaches does not always correspond to the similarity a human user would expect. A way to include more semantic knowledge into the indexing process is to use the text included in the images and video sequences. It is rich in information but easy to use, e.g. by key word based queries. In this paper we present an algorithm to localize artificial text in images and videos using a measure of accumulated gradients and morphological post processing to detect the text. The quality of the localized text is improved by robust multiple frame integration. Anew technique for the binarization of the text boxes is proposed. Finally, detection and OCR results for a commercial OCR are presented.read more
Citations
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A survey on comparision and performance analysis of text extraction techniques
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Proceedings ArticleDOI
Prewett Edge Detector Method for Content Extraction in Moving Pictures or Images
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Video Text Segmentation Using Particle Filters
Datong Chen,Jean-Marc Odobez +1 more
TL;DR: A probabilistic algorithm for segmenting and recognizing text embedded in video sequences based on adaptive thresholding using a Bayes filtering method that allows us to evaluate an text image segmentor on the basis of recognition result instead of visual segmentation result, which is directly relevant to the authors' character recognition task.
Contrast Enhanced Niblack Binarization of Document Images
TL;DR: A method of document image binarization that performs well on grayscale images with complex backgrounds, maintains good text extraction abilities and retains the graphic features that might be present in the image.
References
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IEEE transactions on pattern analysis and machine intelligence
TL;DR: This special issue aims at gathering the recent advances in learning with shared information methods and their applications in computer vision and multimedia analysis and addressing interesting real-world computer Vision and multimedia applications.
Journal ArticleDOI
Goal-directed evaluation of binarization methods
O.D. Trier,Anil K. Jain +1 more
TL;DR: This paper presents a methodology for evaluation of low-level image analysis methods, using binarization (two-level thresholding) as an example, and defines the performance of the character recognition module as the objective measure.
Proceedings ArticleDOI
Automatic text location in images and video frames
Anil K. Jain,Bin Yu +1 more
TL;DR: Compared with some traditional text location methods, this method has the following advantages: 1) low computational cost; 2) robust to font size; and 3) high accuracy.