Accuracy improvement of aerial handwritten katakana character recognition

In this paper, a method of aerial handwritten Japanese katakana character recognition using the triaxial accelerometer is described. The proposed character recognition method is based on k-nearest neighbor (k-NN) algorithm using feature vectors extracted with simple signal processing. From the experiments using dataset for 46 katakana characters from specific perticipant, average recognition rate of 79.6% was confirmed.