TextFinder: An Automatic System to Detect and Recognize Text In Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Recognizing Characters in Scene Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Character Pattern Extraction from Colorful Documents with Complex Backgrounds
ICPR '02 Proceedings of the 16 th International Conference on Pattern Recognition (ICPR'02) Volume 3 - Volume 3
A Robust Approach for Recognition of Text Embedded in Natural Scenes
ICPR '02 Proceedings of the 16 th International Conference on Pattern Recognition (ICPR'02) Volume 3 - Volume 3
Automatic Text Location in Images and Video Frames
ICPR '98 Proceedings of the 14th International Conference on Pattern Recognition-Volume 2 - 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
Wavelet filter evaluation for image compression
IEEE Transactions on Image Processing
Text detection of two major indian scripts in natural scene images
CBDAR'11 Proceedings of the 4th international conference on Camera-Based Document Analysis and Recognition
Segmentation of Bangla words in scene images
Proceedings of the Eighth Indian Conference on Computer Vision, Graphics and Image Processing
Text extraction from natural scene image: A survey
Neurocomputing
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Texts in natural scenes provide us with much useful information. In order to use such information automatically, it is necessary to make computers detect text regions in the images. Gllavata et al. proposed a method based on unsupervised classification of high frequency wavelet coefficients for text detection in video frames [1]. Although the method is very accurate, it does not work so well with some color images, since it lacks the ability of discriminating color difference. This paper proposes an enhanced version of the method. We develop a new unsupervised clustering technique for the classification of multi-channel wavelet features to deal with color images. Experimental results show that the new method yields better results for color scene images.