Adaptive Correcting Strokes Extracted from Chinese Characters in Digital Ink of Non-native Writers Based on Comprehensive Visualization

Abstract

The correcting process for strokes extracted from Chinese characters is the necessary step to extract the errors of writing errors automatically. Visualization of extracted strokes is the prerequisite for manual correction. Therefore, visualization and adaptive correction methods are proposed. To reduce the cognitive burden of correcting, color, brightness, saturation and order number is comprehensively used to visualize extracted strokes. And tag list is applied for correcting different types of extracted strokes, which provides the training set for error extraction classifier in future work. After experimental verification, the method is effective in operational complexity and efficiency.