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Morphology-Based Hierarchical Representation with Application to Text Segmentation in Natural Images

Abstract : Many text segmentation methods are elaborate and thus are not suitable to real-time implementation on mobile devices. Having an efficient and effective method, robust to noise, blur, or uneven illumination, is interesting due to the increasing number of mobile applications needing text extraction. We propose a hierarchical image representation, based on the morphological Laplace operator, which is used to give a robust text segmentation. This representation relies on several very sound theoretical tools; its computation eventually translates to a simple labeling algorithm, and for text segmentation and grouping, to an easy tree-based processing. We also show that this method can also be applied to document binarization, with the interesting feature of getting also reverse-video text.
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https://hal.inria.fr/hal-01476299
Contributor : Thierry Géraud <>
Submitted on : Friday, February 24, 2017 - 4:55:26 PM
Last modification on : Wednesday, June 9, 2021 - 5:28:03 PM
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  • HAL Id : hal-01476299, version 1

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Lê Duy Huỳn, Yongchao Xu, Thierry Géraud. Morphology-Based Hierarchical Representation with Application to Text Segmentation in Natural Images. 23rd International Conference on Pattern Recognition (ICPR), Dec 2016, Cancun, Mexico. ⟨hal-01476299⟩

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