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.

• Type: Conference
• Year: 2002
• Where: ICPR
• Authors: Ergina Kavallieratou, Nikos Fakotakis, George K. Kokkinakis
• Keywords: Character Recognition Algorithm, Computer Vision, ICPR 2002, Inout Radial Profiles, Radial Histogram