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Gamma correction acceleration for real-time text extraction from complex colored images

Abstract : Text extraction from complex colored images involves the suppression of unwanted background while keeping text features. Imaging devices are almost omnipresent and the unrestricted conditions of the images present new challenges for real-time OCR systems. The recently proposed Gamma Correction Method [1] is a robust and good quality method for text extraction in complex colored images. However it requires a large amount of computing resources and is not well suited for real-time applications. In this paper we propose an efficient acceleration of the GCM to drastically reduce its execution-time, while preserving the text extraction quality. Experimental results on ICDAR dataset show that our approach is effective and can reach a speedup of up to 11.430.
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https://hal-upec-upem.archives-ouvertes.fr/hal-01305887
Contributor : Rostom Kachouri <>
Submitted on : Thursday, April 21, 2016 - 10:24:59 PM
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Rostom Kachouri, Christian Armas, Mohamed Akil. Gamma correction acceleration for real-time text extraction from complex colored images. Image Processing (ICIP) 2015, Sep 2015, Quebec City, QC, Canada. ⟨10.1109/ICIP.2015.7350854⟩. ⟨hal-01305887⟩

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