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• W1032917029 abstract "The research described in this paper focuses on the presentation of two novel preprocessing techniques for the task of off-line handwritten word recognition. A technique for the identification of straight and skewed underline noise is described along with a novel algorithm for detecting skew in handwritten words. The latter identifies skew by detecting the center of mass in each half of a word image. By hypothesizing a line between the two centres and by measuring the angle it makes with the x-axis, an angle for skew may be estimated. The algorithms are tested on the CEDAR benchmark database of handwritten cursive words. Results above 96% are reported for skew detection and underline removal." @default.
• W1032917029 created "2016-06-24" @default.
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• W1032917029 date "2002-01-01" @default.
• W1032917029 modified "2023-09-23" @default.
• W1032917029 title "New Preprocessing Techniques for Handwritten Word Recognition" @default.
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