Detection, Localization of Text in Images by Mser and Enhanced Swt
S. Shiyamala1, S. Suganya2
1Mrs. S. Shiyamala, Pursued M.SC., M. Phil., in Computer Science from Bharathiar University, Coimbatore.
2S. Suganya, Associate Professor, Department of Computer Science, Rathnavel Subramaniam College of arts and Science, Sulur, Coimbatore
Manuscript received on 15 August 2019 | Revised Manuscript received on 21 August 2019 | Manuscript published on 30 August 2019 | PP: 2873-2875 | Volume-8 Issue-10, August 2019 | Retrieval Number: J96120881019/2019©BEIESP | DOI: 10.35940/ijitee.J9612.0881019
Open Access | Ethics and Policies | Cite | Mendeley | Indexing and Abstracting
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: The number digital images and digital videos has raised highly. The text shows in the images is major thing for fully understanding the images. So it is very signifigant to recognize the text. First step of text recognization system is known as text detection. But detecting text from images is very challenging and it is receiving high amount of concentration. Text detection is improved by pre-procssing techniques like noise removal, contrast changes and etc. Recently MSER (Maximally Stable Edge Region) and SWT (Stroke Width Transformation) methods are used seperately or combined with each other for detecting and localizing text. This paper analyzes and compares technical challenges and performance of above methods and take in new and fast method for text detection and localization. The proposed method comprises an enhanced technique based on SWT which combined with MSER. The proposed method detect wording which is located in differnt directions, different angle and combined letters. Performance of exisisting and proposed methods on road signal images depicted in experimental results.
Keywords: MSER, SWT, Canny Edge Detection
Scope of the Article: Image Security