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Text/Graphics Separation for Business Card Images for Mobile Devices
Separation of the text regions from background texture and graphics is a...
04/06/2010 ∙ by Ayatullah Faruk Mollah, et al. ∙
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Text/Graphics Separation and Skew Correction of Text Regions of Business Card Images for Mobile Devices
Separation of the text regions from background texture and graphics is a...
02/21/2010 ∙ by Ayatullah Faruk Mollah, et al. ∙
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Text Region Extraction from Business Card Images for Mobile Devices
Designing a Business Card Reader (BCR) for mobile devices is a challenge...
03/02/2010 ∙ by Ayatullah Faruk Mollah, et al. ∙
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Tabular Structure Detection from Document Images for Resource Constrained Devices Using A Row Based Similarity Measure
Tabular structures are used to present crucial information in a structur...
08/26/2020 ∙ by Soumyadeep Dey, et al. ∙
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Brno Mobile OCR Dataset
We introduce the Brno Mobile OCR Dataset (B-MOD) for document Optical Ch...
07/02/2019 ∙ by Martin Kišš, et al. ∙
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Locally Non-rigid Registration for Mobile HDR Photography
Image registration for stack-based HDR photography is challenging. If no...
04/07/2015 ∙ by Orazio Gallo, et al. ∙
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A Survey on Ransomware: Evolution, Taxonomy, and Defense Solutions
In recent years, ransomware has been one of the most notorious malware t...
02/11/2021 ∙ by Harun Oz, et al. ∙
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Binarizing Business Card Images for Mobile Devices
03/02/2010 ∙ by Ayatullah Faruk Mollah, et al. ∙
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Business card images are of multiple natures as these often contain graphics, pictures and texts of various fonts and sizes both in background and foreground. So, the conventional binarization techniques designed for document images can not be directly applied on mobile devices. In this paper, we have presented a fast binarization technique for camera captured business card images. A card image is split into small blocks. Some of these blocks are classified as part of the background based on intensity variance. Then the non-text regions are eliminated and the text ones are skew corrected and binarized using a simple yet adaptive technique. Experiment shows that the technique is fast, efficient and applicable for the mobile devices.
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