PReMI '09 Proceedings of the 3rd International Conference on Pattern Recognition and Machine Intelligence
Image segmentation algorithms based on the machine learning of features
Pattern Recognition Letters
Text detection in images using sparse representation with discriminative dictionaries
Image and Vision Computing
Two-channel nonseparable wavelets statistically matched to 2-D images
Signal Processing
Assistive text reading from complex background for blind persons
CBDAR'11 Proceedings of the 4th international conference on Camera-Based Document Analysis and Recognition
Text extraction from scene images by character appearance and structure modeling
Computer Vision and Image Understanding
Content directed enhancement of degraded document images
Proceeding of the workshop on Document Analysis and Recognition
Inscription extraction from Traditional Chinese Painting images
Proceedings of the Fifth International Conference on Internet Multimedia Computing and Service
International Journal of Computer Vision and Image Processing
Text graphic separation in Indian newspapers
Proceedings of the 4th International Workshop on Multilingual OCR
Research on born-digital image text extraction based on conditional random field
International Journal of High Performance Systems Architecture
Hi-index | 0.01 |
In this paper, we have proposed a novel scheme for the extraction of textual areas of an image using globally matched wavelet filters. A clustering-based technique has been devised for estimating globally matched wavelet filters using a collection of groundtruth images. We have extended our text extraction scheme for the segmentation of document images into text, background, and picture components (which include graphics and continuous tone images). Multiple, two-class Fisher classifiers have been used for this purpose. We also exploit contextual information by using a Markov random field formulation-based pixel labeling scheme for refinement of the segmentation results. Experimental results have established effectiveness of our approach.