On Handwriting Recognition System Performance: Some Experimental Results

Abstract

Performance of a rule-based handwriting recognition system is considered. Performance limits of such systems are defined by the robustness of the character templates and the ability of the system to segment characters. Published performance figures, however, are typically based on pre-segmented characters. Six experiments are reported (using a total of 128 subjects) that tested a state-of-the-art recognition system under more realistic conditions. Variables investigated include display format (grid, lined, and blank), surface texture, feedback (location and time delay), amount of training, practice, and effects of use over an extended period. Results indicated that novice users writing on a lined display (the most preferred format) averaged 57% recognition performance. By giving subjects continuous feedback of results, training, and after about 10 minutes of use, the system averaged 90.6% character recognition. Following three hours of interrupted use and with performance incentives, subjects achieved an average 96.8% accuracy with the system. Future work should focus on improving the ability of the recognition algorithm to segment characters and on developing non-obtrusive interaction techniques to train users, to provide feedback and to correct mis-recognized characters.