Segmentation and recognition of handwritten characters using subspace method

Segmentation of characters freely written on papers is a difficult problem for a computer system. Conventionally this problem has been dealt with by image processing such os horizontal or vertical projection. But it sometimes splits and merges the character images and fails to correctly segment them, due to its lack of character recognition ability in the segmentation process. We propose in this paper a method to solve this problem by performing character recognition in segmentation process based on a subspace method. At first, a binary image on which characters are written, is scanned by a fixed sale of a window. At every scanning location, 196(7×7×4) features are obtained and projected to each character subspace. The character recognition using subspace method is carried out and character name (or group name) and its confidence are obtained. Since this character segmentation based on the subspace method performs the character recognition simultaneously, it can be applied to isolatedly or cursively written characters