Paper
17 March 2017 A framework of text detection and recognition from natural images for mobile device
Zied Selmi, Mohamed Ben Halima, Ali Wali, Adel M. Alimi
Author Affiliations +
Proceedings Volume 10341, Ninth International Conference on Machine Vision (ICMV 2016); 1034127 (2017) https://doi.org/10.1117/12.2268567
Event: Ninth International Conference on Machine Vision, 2016, Nice, France
Abstract
On the light of the remarkable audio-visual effect on modern life, and the massive use of new technologies (smartphones, tablets ...), the image has been given a great importance in the field of communication. Actually, it has become the most effective, attractive and suitable means of communication for transmitting information between different people. Of all the various parts of information that can be extracted from the image, our focus will be particularly on the text. Actually, since its detection and recognition in a natural image is a major problem in many applications, the text has drawn the attention of a great number of researchers in recent years. In this paper, we present a framework for text detection and recognition from natural images for mobile devices.
© (2017) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Zied Selmi, Mohamed Ben Halima, Ali Wali, and Adel M. Alimi "A framework of text detection and recognition from natural images for mobile device", Proc. SPIE 10341, Ninth International Conference on Machine Vision (ICMV 2016), 1034127 (17 March 2017); https://doi.org/10.1117/12.2268567
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Cited by 1 scholarly publication.
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KEYWORDS
Image filtering

Image segmentation

Optical character recognition

Mobile devices

Detection and tracking algorithms

Cameras

Feature extraction

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