IMPROVING THE IMAGE BINARIZATION PROCESS BY USING A WEIGHTED-VOTING SCHEME

Cristian-Daniel Pobleanu (), Andrei Dumitrescu (), Ștefania Cristea () and Giorgiana Violeta Vlăsceanu ()
Additional contact information
Cristian-Daniel Pobleanu: University Politehnica of Bucharest, Bucharest, Romania
Andrei Dumitrescu: University Politehnica of Bucharest, Bucharest, Romania
Ștefania Cristea: University Politehnica of Bucharest, Bucharest, Romania
Giorgiana Violeta Vlăsceanu: University Politehnica of Bucharest, Bucharest, Romania

Journal of Information Systems & Operations Management, 2020, vol. 14, issue 2, 160-169

Abstract: An essential step in the OCR (Optical Character Recognition) flow is the stage of image binarization. There are considerable algorithms used for the stage of binarization. The significant difference between them is the method that computes the pixel threshold value. These algorithms can categorize into two groups: those that require a single threshold value for the whole image (which can recognize larger areas or objects) and those that use a threshold obtained from the pixel’s local space (pixels in the neighborhood of the given pixel and that can identify smaller clusters of pixels). The objective of this paper is to present a voting-based image binarization algorithm that makes use of results from both categories of algorithms previously mentioned.

Date: 2020
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www.rebe.rau.ro/RePEc/rau/jisomg/WI20/JISOM-WI20-A15.pdf (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:rau:jisomg:v:14:y:2020:i:2:p:160-169

Access Statistics for this article

More articles in Journal of Information Systems & Operations Management from Romanian-American University Contact information at EDIRC.
Bibliographic data for series maintained by Alex Tabusca ().