Document Type : Methodologies

Authors

Faculty of Engineering and Technology, Alzahra University, Tehran, Iran.

10.22044/jadm.2022.11089.2260

Abstract

Digital images are being produced in a massive number every day. A

component that may exist in digital images is text. Textual information can be

extracted and used in a variety of fields. Noise, blur, distortions, occlusion, font

variation, alignments, and orientation, are among the main challenges for text

detection in natural images. Despite many advances in text detection algorithms,

there is not yet a single algorithm that addresses all of the above problems

successfully. Furthermore, most of the proposed algorithms can only detect

horizontal texts and a very small fraction of them consider Farsi language. In

this paper, a method is proposed for detecting multi-orientated texts in both Farsi

and English languages. We have defined seven geometric features to distinguish

text components from the background and proposed a new contrast enhancement

method for text detection algorithms. Our experimental results indicate that the

proposed method achieves a high performance in text detection on natural images.

Keywords

Main Subjects

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