Document image binarization preserving stroke connectivity

Il Seok Oh

doi:10.1016/0167-8655(95)00014-8

Document image binarization preserving stroke connectivity

Il Seok Oh^*

^*Corresponding author for this work

Research output: Contribution to journal › Journal article › peer-review

6 Scopus citations

Abstract

The local comparison technique is widely used for document image binarization due to its superiority to other techniques in extracting the strokes from a gray-scale document image containing spatially uneven gray-levels. In this paper, we identify one weak point of the technique, being not good in preserving the stroke connectivity. After analyzing the reason for it, we present two new schemes which greatly improve the stroke connectivity. We prove the effectiveness of our solution through experimental results.

Original language	English
Pages (from-to)	743-748
Number of pages	6
Journal	Pattern Recognition Letters
Volume	16
Issue number	7
DOIs	https://doi.org/10.1016/0167-8655(95)00014-8
State	Published - 1995.07

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

Keywords

Character recognition
Document image binarization
Local comparison algorithm
Stroke connectivity

Access to Document

10.1016/0167-8655(95)00014-8

Cite this

@article{2e04895796384a46a8ced392a1088903,

title = "Document image binarization preserving stroke connectivity",

abstract = "The local comparison technique is widely used for document image binarization due to its superiority to other techniques in extracting the strokes from a gray-scale document image containing spatially uneven gray-levels. In this paper, we identify one weak point of the technique, being not good in preserving the stroke connectivity. After analyzing the reason for it, we present two new schemes which greatly improve the stroke connectivity. We prove the effectiveness of our solution through experimental results.",

keywords = "Character recognition, Document image binarization, Local comparison algorithm, Stroke connectivity",

author = "Oh, \{Il Seok\}",

year = "1995",

month = jul,

doi = "10.1016/0167-8655(95)00014-8",

language = "English",

volume = "16",

pages = "743--748",

journal = "Pattern Recognition Letters",

issn = "0167-8655",

number = "7",

}

TY - JOUR

T1 - Document image binarization preserving stroke connectivity

AU - Oh, Il Seok

PY - 1995/7

Y1 - 1995/7

N2 - The local comparison technique is widely used for document image binarization due to its superiority to other techniques in extracting the strokes from a gray-scale document image containing spatially uneven gray-levels. In this paper, we identify one weak point of the technique, being not good in preserving the stroke connectivity. After analyzing the reason for it, we present two new schemes which greatly improve the stroke connectivity. We prove the effectiveness of our solution through experimental results.

AB - The local comparison technique is widely used for document image binarization due to its superiority to other techniques in extracting the strokes from a gray-scale document image containing spatially uneven gray-levels. In this paper, we identify one weak point of the technique, being not good in preserving the stroke connectivity. After analyzing the reason for it, we present two new schemes which greatly improve the stroke connectivity. We prove the effectiveness of our solution through experimental results.

KW - Character recognition

KW - Document image binarization

KW - Local comparison algorithm

KW - Stroke connectivity

UR - https://www.scopus.com/pages/publications/0029344258

U2 - 10.1016/0167-8655(95)00014-8

DO - 10.1016/0167-8655(95)00014-8

M3 - Journal article

AN - SCOPUS:0029344258

SN - 0167-8655

VL - 16

SP - 743

EP - 748

JO - Pattern Recognition Letters

JF - Pattern Recognition Letters

IS - 7

ER -

Document image binarization preserving stroke connectivity

Abstract

UN SDGs

Keywords

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