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A new hybrid binarization method based on Kmeans
Mahmoud Soua, Rostom Kachouri, Mohamed Akil

A new hybrid binarization method based on Kmeans

Science & Mathematics Published 2014 Verification Pending

Overview & Synopsis

The document binarization is a fundamental processing step toward Optical Character Recognition (OCR). It aims to separate the foreground text from the document background. In this article, we propose a novel binarization technique combining local and global approaches using the clustering algorithm Kmeans. The proposed Hybrid Binarization, based on Kmeans (HBK), performs a robust binarization on scanned documents. According to several experiments, we demonstrate that the HBK method improves the binarization quality while minimizing the amount of distortion. Moreover, it out-performs several well-known state of the art methods in the OCR evaluation.

Indexed from repository: HAL Open Science (hal.science)
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Document Information

Document Title A new hybrid binarization method based on Kmeans
Author / Organization Mahmoud Soua, Rostom Kachouri, Mohamed Akil
Subject & Discipline Multidisciplinary Academic Open Research
Categories Science & Mathematics
Publication Year 2014
License / Rights Open Access / Creative Commons
Resource Verification Listed PDF (Verification Pending)
Original Host Website HAL Open Science (hal.science)
File Format application/pdf (Portable Document Format)
Language EN
Catalog ID DOC-155763
Original Source Link Visit Source Page on hal.science »