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ICPR
2002
IEEE

Handwritten Character Recognition Based on Structural Characteristics

12 years 7 months ago
Handwritten Character Recognition Based on Structural Characteristics
In this paper a handwritten character recognition algorithm based on structural characteristics, histograms and profiles, is presented. The well-known horizontal and vertical histograms are used, in combination with the newly introduced radial histogram, out-in radial and inout radial profiles for representing 32x32 matrices of characters, as 280-dimension vectors. The K-means algorithm is used for the classification of these vectors. Detailed experiments performed in NIST and GRUHD databases gave promising accuracy results that vary from 72.8% to 98.8% depending on the difficulty of the database and the character category.
Ergina Kavallieratou, Nikos Fakotakis, George K. K
Added 09 Nov 2009
Updated 09 Nov 2009
Type Conference
Year 2002
Where ICPR
Authors Ergina Kavallieratou, Nikos Fakotakis, George K. Kokkinakis
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