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Reseach Article

Extracting and Segmenting Container Name from Container Images

by M. M. Aftab Chowdhury, Kaushik Deb
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 74 - Number 19
Year of Publication: 2013
Authors: M. M. Aftab Chowdhury, Kaushik Deb
10.5120/13001-0039

M. M. Aftab Chowdhury, Kaushik Deb . Extracting and Segmenting Container Name from Container Images. International Journal of Computer Applications. 74, 19 ( July 2013), 18-22. DOI=10.5120/13001-0039

@article{ 10.5120/13001-0039,
author = { M. M. Aftab Chowdhury, Kaushik Deb },
title = { Extracting and Segmenting Container Name from Container Images },
journal = { International Journal of Computer Applications },
issue_date = { July 2013 },
volume = { 74 },
number = { 19 },
month = { July },
year = { 2013 },
issn = { 0975-8887 },
pages = { 18-22 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume74/number19/13001-0039/ },
doi = { 10.5120/13001-0039 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:42:43.137117+05:30
%A M. M. Aftab Chowdhury
%A Kaushik Deb
%T Extracting and Segmenting Container Name from Container Images
%J International Journal of Computer Applications
%@ 0975-8887
%V 74
%N 19
%P 18-22
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Container name extraction is very important to the modern container management system. Similar techniques have been suggested for vehicle license plate recognition in past decades. Container name extraction has more complexity from license plate extraction because of the severity of nonuniform illumination and invalidation of color information. The main purpose of this paper is to propose a new methodology for text extraction,segmenting text characters and removing non text,background from images. Existing text extraction methods do not work efficiently in case of images with noice and complex background. Documents with only text work efficiently in OCR. The approach used is based on edge detection,close operation,detecting connected components,removing non text regions and character segmentation.

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Index Terms

Computer Science
Information Sciences

Keywords

Mathematical Morphology Morphological Operators Edge detection Localization Connected Component