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In this paper, a novel script-independent block-based text line extraction technique is proposed for multi-skewed document images. Three parameters are defined to adopt the method with various writings. Extensive experiments on different datasets demonstrate that the proposed algorithm outperforms previous methods.
In this paper, we propose a new approach for detecting and recognizing numerical strings in Farsi/Arabic handwritten or machine-printed document images. We assign a label to each of the connected components as they belong to a numerical string or not. First, in order to differentiate between digit and non-digit connected components, some simple features are extracted from all connected components...
Standard databases play very important roles in pattern recognition tasks. To compare the performances of different algorithms, they must be tested on a same dataset. In Farsi, there is not a database of handwritten texts to evaluate different algorithms. In this paper, an unconstraint Farsi handwritten text database is introduced. 250 participants in different ages and education levels filled 1000...
In this paper, a preprocessing block for the middle-age Persian documents is proposed. The main idea is based on the mathematical morphology, connected components and clustering. The proposed algorithm is capable to simultaneously remove the noise and segment the manuscript to its basic components i.e. lines, words and characters. The proposed strategy has been tested on 200 page of the middle-age...
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