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Logo detection in Arabic documents using multi smearing method and decision tree
Other Title(s)
الكشف عن الشعار في الوثائق العربية باستخدام طريقة التلطيخ المتعدد و شجرة اتخاذ القرار
Joint Authors
Abbas, Haytham Karim
Abd al-Munim, Mathil Imad al-Din
Source
Issue
Vol. 2017, Issue 27 (30 Jun. 2017), pp.1-14, 14 p.
Publisher
Publication Date
2017-06-30
Country of Publication
Iraq
No. of Pages
14
Main Subjects
Information Technology and Computer Science
Topics
Abstract EN
The detection of logo techniques play significant role for document image analysis and retrieval.
In this paper, an effective logo detection method in Arabic document images has been proposed.
In the proposed technique different logos can be detected based on extracting features that will distinguish logo from other non-logo parts of document like text, graph, table, and also stamp.
This model is divided into three main stages.
The first stage is smearing stage, where the document image has been smeared in multi directions to segment image to different blocks represent foreground objects of document.
The second stage is to extract appropriate and significant features from these blocks by bounding blocks into rectangles.
The third stage is performing decision tree that consist of a number of rules that will be applied to block features to correctly classify logo from non-logo objects.
The proposed technique overcome many problem of logo detection like logos that contains separated parts, logos with text, and logo with noise.
This technique has been tested and evaluated on dataset containing variety of Arabic document images of different colors, shapes and resolutions.
Experimental results exhibit its performance in detecting logos with 96% for accuracy and 98% for precision.
American Psychological Association (APA)
Abd al-Munim, Mathil Imad al-Din& Abbas, Haytham Karim. 2017. Logo detection in Arabic documents using multi smearing method and decision tree. al-Mansour،Vol. 2017, no. 27, pp.1-14.
https://search.emarefa.net/detail/BIM-779031
Modern Language Association (MLA)
Abd al-Munim, Mathil Imad al-Din& Abbas, Haytham Karim. Logo detection in Arabic documents using multi smearing method and decision tree. al-Mansour No. 27 (2017), pp.1-14.
https://search.emarefa.net/detail/BIM-779031
American Medical Association (AMA)
Abd al-Munim, Mathil Imad al-Din& Abbas, Haytham Karim. Logo detection in Arabic documents using multi smearing method and decision tree. al-Mansour. 2017. Vol. 2017, no. 27, pp.1-14.
https://search.emarefa.net/detail/BIM-779031
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references : p. 12-13
Record ID
BIM-779031