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This paper deals with the problem of recognizing accented and non-accented characters in French handwriting. Accented characters increase the number of classes to be recognized. The performances of powerful classifier such as SVM are declined by the presence of accents. In this paper, an accented character is segmented into two parts: the root character or letter and the accent. These two parts are...
Recently a new method for recognition of isolated handwritten Persian digits, based on support vector machines (SVMs), has been introduced. In this research, this method was implemented for the same task with three new modifications, i.e. only one popular shape was considered for digits written in different shapes; sizes of glyphs normalized to digit boundaries; MLP (multi-layer perceptron), SVM/MLP...
In this paper, we propose two types of feature sets based on modified chain-code direction frequencies in the contour pixels of input image and modified transition features (horizontally and vertically). A multi-level support vector machine (SVM) is proposed as classifier to recognize Persian isolated digits. In first level, we combine similar shaped numerals into a single group and as result; we...
In this paper we investigate the use of linguistic information given by language models to deal with word recognition errors on handwritten sentences. We focus especially on errors due to out-of-vocabulary (OOV) words. First, word posterior probabilities are computed and used to detect error hypotheses on output sentences. An SVM classifier allows these errors to be categorized according to defined...
Transforming handwriting into digital text and recognition of handwritten patterns opens a vast scope of application opportunities from searching for handwritten notes and document management to causing actions by writing symbols. Despite receiving a great attention, a massive number of applications, and a huge research effort, recognition of handwritten text has not still reached a desired efficiency...
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