scholarly journals Multi-Oriented Text Detection in Natural Scene Images Based on the Intersection of MSER With the Locally Binarized Image

2020 ◽  
Vol 171 ◽  
pp. 322-330 ◽  
Author(s):  
Anurag Agrahari ◽  
Rajib Ghosh
Keyword(s):  
Text Detection ◽  
Natural Scene ◽  
Natural Scene Images ◽  
Binarized Image

Devanagari Text Detection From Natural Scene Images

2020 ◽  
Vol 10 (3) ◽  
pp. 44-59
Author(s):  
Sankirti Sandeep Shiravale ◽  
R. Jayadevan ◽  
Sanjeev S. Sannakki
Keyword(s):  
Edge Detection ◽  
Image Understanding ◽  
Text Detection ◽  
Experimental Results ◽  
Combined Approach ◽  
Natural Scene ◽  
Light Conditions ◽  
The Individual ◽  
Natural Scene Images ◽  
Better Than

Text present in a camera captured scene images is semantically rich and can be used for image understanding. Automatic detection, extraction, and recognition of text are crucial in image understanding applications. Text detection from natural scene images is a tedious task due to complex background, uneven light conditions, multi-coloured and multi-sized font. Two techniques, namely ‘edge detection' and ‘colour-based clustering', are combined in this paper to detect text in scene images. Region properties are used for elimination of falsely generated annotations. A dataset of 1250 images is created and used for experimentation. Experimental results show that the combined approach performs better than the individual approaches.

A robust arbitrary text detection system for natural scene images

2014 ◽  
Vol 41 (18) ◽  
pp. 8027-8048 ◽  
Author(s):  
Anhar Risnumawan ◽  
Palaiahankote Shivakumara ◽  
Chee Seng Chan ◽  
Chew Lim Tan
Keyword(s):  
Detection System ◽  
Text Detection ◽  
Natural Scene ◽  
Natural Scene Images

Multilingual Scene Text Detection Using Gradient Morphology

2020 ◽  
Vol 10 (3) ◽  
pp. 31-43 ◽  
Author(s):  
Dibyajyoti Dhar ◽  
Neelotpal Chakraborty ◽  
Sayan Choudhury ◽  
Ashis Paul ◽  
Ayatullah Faruk Mollah ◽  
...  
Keyword(s):  
State Of The Art ◽  
High Sensitivity ◽  
Text Detection ◽  
Interesting Problem ◽  
Natural Scene ◽  
The Past ◽  
Scene Text Detection ◽  
Scene Text ◽  
Multiple Languages ◽  
Natural Scene Images

Text detection in natural scene images is an interesting problem in the field of information retrieval. Several methods have been proposed over the past few decades for scene text detection. However, the robustness and efficiency of these methods are downgraded due to high sensitivity towards various complexities of an image. Also, in multi-lingual environment where texts may occur in multiple languages, a method may not be suitable for detecting scene texts in certain languages. To counter these challenges, a gradient morphology-based method is proposed in this paper that proves to be robust against image complexities and efficiently detects scene texts irrespective of their languages. The method is validated using low quality images from standard multi-lingual datasets like MSRA-TD500 and MLe2e. The performance of the method is compared with that of some state-of-the-art methods, and comparably better results are observed.

Text detection in natural scene images with user-intention

2013 ◽  
Author(s):  
Liuan Wang ◽  
Yutaka Katsuyama ◽  
Wei Fan ◽  
Yuan He ◽  
Jun Sun ◽  
...  
Keyword(s):  
Text Detection ◽  
Natural Scene ◽  
User Intention ◽  
Natural Scene Images

Arbitrarily-Oriented Text Detection in Low Light Natural Scene Images

2020 ◽  
pp. 1-1 ◽  
Author(s):  
Minglong Xue ◽  
Palaiahnakote Shivakumara ◽  
Chao Zhang ◽  
Yao Xiao ◽  
Tong Lu ◽  
...  
Keyword(s):  
Text Detection ◽  
Natural Scene ◽  
Low Light ◽  
Natural Scene Images
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