Real-time shape recognition scheme on projected capacitive touchscreens

Most modern mobile devices are equipped with touchscreens as the main input hardware. Users can write text or draw shapes on the touchscreen to interact with apps. Therefore, accurate recognition of users’ freehand sketches becomes crucial for a device to receive correct instructions from users. This paper proposes a real-time scheme to recognize shapes drawn on the touchscreen. The proposed shape recognition scheme includes preprocessing, feature extraction and shape classification stages. Freehand strokes drawn by users are usually distorted and inaccurate. In preprocessing, this study uses the sampling technique to remove drawing imperfections such as small jagged noise or distorted strokes. In the feature extraction, we use a state machine to extract the length and curvature as the intrinsic features of a shape. In the final shape classification stage, a template-based approach is used to classify the input shape. A fitness score of the input shape to a template is calculated and the template with the highest score is chosen as the most matched shape. Experiment results show that the proposed real-time shape recognition has high accuracy and good performance.