Progress in Camera-Based Document Image Analysis
ICDAR '03 Proceedings of the Seventh International Conference on Document Analysis and Recognition - Volume 1
Low resolution character recognition by dual eigenspace and synthetic degraded patterns
Proceedings of the 1st ACM workshop on Hardcopy document processing
Video text recognition using sequential Monte Carlo and error voting methods
Pattern Recognition Letters
Camera based Degraded Text Recognition Using Grayscale Feature
ICDAR '05 Proceedings of the Eighth International Conference on Document Analysis and Recognition
Gabor filters-based feature extraction for character recognition
Pattern Recognition
Display text segmentation after learning best-fitted OCR binarization parameters
Expert Systems with Applications: An International Journal
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We propose a new high-speed, high-accuracy binarization method for recognizing text in document images. First, character neighborhoods are extracted from input images using a global thresholding value that is shifted to the background pixel value from the thresholding value of conventional global binarization.Second, characters are extracted using an original local binarization process integrated with image interpolation. Our method takes only 1/100 the processing time over the method that performs image interpolation first. Therefore our method binalizes an A4 size text image (150dpi) in an average of only 3.3 seconds using a 166 MHz Pentium processor. Furthermore, our method reduced unrecognized characters by 46.5%, compared with conventional global binarization.