A new efficient text detection method for image spam filtering

Al Muataz, Zubaidah and Abdul Aziz, Normaziah (2015) A new efficient text detection method for image spam filtering. International Review on Computers and Software, 10 (1). pp. 1-8. ISSN 1828-6003

PDF Restricted to Repository staff only Download (2MB) | Request a copy

Abstract

Detection of text in images plays an important role in many situations such as video retrieval, annotation, indexing, and content analysis. In information security to filter image spam, one main feature can be used is text contents in image. Extracting text features from image spam needs efficient text detection. Obfuscating techniques used by spammers such as noisy background, wavy text and text with different colors pose challenges to the text detection process. In this paper, we present a text detection method that addresses these challenges. The contribution of this research consists of two parts: a) a new edge operator can specifically be used to detect text edges, and b) proposing of text detection method for image spam filtering that can detect obfuscated text. The proposed method Accumulated Text Extraction (ATE) works for detecting horizontal and vertical lines and intersecting them, then rules are used to determine the text area and reduce non text area. The approach focuses on using non-machine learning methods with simple calculations. ATE shows encouraging results which can be efficiently used in image spam filtering. Besides its robustness against obfuscating methods in image spam, ATE shows efficient performance when used for scene text detection.

Item Type:	Article (Journal)
Additional Information:	5505/48601
Uncontrolled Keywords:	Text Detection, Image Spam, Obfuscation Text, Security, Edge Operator, Intersection, Rule-Based, Horizontal and Vertical Lines
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button):	Kulliyyah of Information and Communication Technology > Department of Computer Science Kulliyyah of Information and Communication Technology > Department of Computer Science
Depositing User:	Dr. Normaziah Abdul Aziz
Date Deposited:	19 Jan 2016 14:49
Last Modified:	06 Jun 2016 03:30
URI:	http://irep.iium.edu.my/id/eprint/48601

Actions (login required)

View Item