A Computational Approach to Edge Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Distance transformations in digital images
Computer Vision, Graphics, and Image Processing
ICDAR 2003 Robust Reading Competitions
ICDAR '03 Proceedings of the Seventh International Conference on Document Analysis and Recognition - Volume 2
Text Detection in Images Based on Unsupervised Classification of High-Frequency Wavelet Coefficients
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 1 - Volume 01
Text Detection from Natural Scene Images: Towards a System for Visually Impaired Persons
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 2 - Volume 02
ICDAR '05 Proceedings of the Eighth International Conference on Document Analysis and Recognition
Character-Stroke Detection for Text-Localization and Extraction
ICDAR '07 Proceedings of the Ninth International Conference on Document Analysis and Recognition - Volume 01
Devanagari and Bangla Text Extraction from Natural Scene Images
ICDAR '09 Proceedings of the 2009 10th International Conference on Document Analysis and Recognition
Fast and robust text detection in images and video frames
Image and Vision Computing
Bangla/English script identification based on analysis of connected component profiles
DAS'06 Proceedings of the 7th international conference on Document Analysis Systems
Automatic text detection and tracking in digital video
IEEE Transactions on Image Processing
Segmentation of Bangla words in scene images
Proceedings of the Eighth Indian Conference on Computer Vision, Graphics and Image Processing
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In this article, we present a robust scheme for detection of Devanagari or Bangla texts in scene images. These are the two most popular scripts in India. The proposed scheme is primarily based on two major characteristics of such texts - (i) variations in stroke thickness for text components of a script are low compared to their non-text counterparts and (ii) presence of a headline along with a few vertical downward strokes originating from this headline. We use the Euclidean distance transform to verify the general characteristics of texts in (i). Also, we apply the probabilistic Hough line transform to detect the characteristic headline of Devanagari and Bangla texts. Further, similarity and adjacency measures are applied to identify text regions, which do not satisfy the verification in (ii). The proposed approach has been simulated on a repository of 120 images taken from Indian roads and the results are encouraging. Also, we have discussed the applicability of the proposed scheme for detection of English texts. Towards this end, we have considered the training and test samples from the image database of ICDAR 2003 Robust Reading Competition.