A new hybrid binarization method based on Kmeans
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
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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 » |