Proceedings ArticleDOI
Adaptive method for multi colored text binarization
Arindam Das,Sandipan Chowdhury +1 more
- pp 1-5
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TLDR
The main novelty of this reported work includes the calculation of each edge box based local color threshold value from CIELAB color space that makes the proposed system capable of binarizing multi colored texts where a single character has more than one color.Abstract:
This article presents our recent study on multi colored text binarization. In the output image, we represented foreground content as black and background as white regardless the polarity of foreground and background in original image. Here we applied connected component analysis based approach to group the words or characters within bounding or edge box. The main novelty of this reported work includes the calculation of each edge box based local color threshold value from CIELAB color space. This approach makes the proposed system capable of binarizing multi colored texts where a single character has more than one color. The proposed method has been executed on well-known D1BCO2009 and CMATERdb datasets that contain a large set of images to show the efficiency over other existing methods through qualitative comparison study.read more
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Journal Article
Novel Approach for Image Binarization Using Genetic Algorithm
TL;DR: This research work, the technique of genetic algorithm is applied which define the threshold value for the image binarization and it is analyzed that proposed algorithm performs well in terms of all parameters.
References
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Journal ArticleDOI
A Computational Approach to Edge Detection
TL;DR: There is a natural uncertainty principle between detection and localization performance, which are the two main goals, and with this principle a single operator shape is derived which is optimal at any scale.
Journal ArticleDOI
Adaptive document image binarization
Jaakko Sauvola,Matti Pietikäinen +1 more
TL;DR: A new method is presented for adaptive document image binarization, where the page is considered as a collection of subcomponents such as text, background and picture, which adapts and performs well in each case qualitatively and quantitatively.
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