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In this paper, we propose a novel post processing approach for on-line handwriting recognition. Differing from the existing linguistic knowledge-based methods, we make use of domain specific knowledge to improve the performance of recognition. Our system recognizes doctor's handwriting which often poses great challenges in readability, and then enhances the quality of recognized text by analyzing...
This paper introduces a binarization method based on edge for video text images, especially for images with complex background or low contrast. The binarization method first detects the contour of the text, and utilizes a local thresholding method to decide the inner side of the contour, and then fills up the contour to form characters that are recognizable to OCR software. Experiment results show...
This paper presents a language identification technique that detects Latin-based languages of imaged documents without OCR. The proposed technique detects languages through the word shape coding, which converts each word image into a word shape code and accordingly transforms each document image into an electronic document vector. For each Latin-based language under study, a language template is first...
Categorization of imaged documents is a useful technique for building document image based digital libraries. This paper investigates techniques to improve categorization accuracy on OCR text, particularly that of biomedical imaged documents. Experiments with different feature selection methods were run to explore their effect on the categorization performance. The result shows that document frequency...
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