Text segmentation and recognition in complex background based on Markov random field

In this paper we propose a method to segment and recognize text embedded in video and images. We modelize the gray level distribution in the text images as mixture of gaussians, and then assign each pixel to one of the gaussian layer. The assignment is based on prior of the contextual information, w...

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Bibliographic Details
Main Authors: Datong Chen, Olobez, J.-M., Bourlard, H.
Format: Conference Proceeding
Language:English
Subjects:
Filters
Gaussian distribution
Gray-scale
Image edge detection
Image recognition
Image segmentation
Markov random fields
Optical character recognition software
Pixel
Text recognition
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Description
Summary:In this paper we propose a method to segment and recognize text embedded in video and images. We modelize the gray level distribution in the text images as mixture of gaussians, and then assign each pixel to one of the gaussian layer. The assignment is based on prior of the contextual information, which is modeled by a Markov random field (MRF) with online estimated coefficients. Each layer is then processed through a connected component analysis module and forwarded to the OCR system as one segmentation hypothesis. By varying the number of gaussians, multiple hypotheses are provided to an OCR system and the final result is selected from the set of outputs, leading to an improvement of the system's performances.
ISSN:1051-4651
2831-7475
DOI:10.1109/ICPR.2002.1047438