Improved error-correcting from extracted handwritings in Chinese

Hao Bai

doi:10.1117/12.2604703

6 August 2021 Improved error-correcting from extracted handwritings in Chinese

Hao Bai

Proceedings Volume 11913, Sixth International Workshop on Pattern Recognition; 119130D (2021) https://doi.org/10.1117/12.2604703
Event: Sixth International Workshop on Pattern Recognition, 2021, Chengdu, China

Abstract

Errors exist in extracted Chinese handwritings even importing language models because of casualness and diversity of handwriting input, which would also affect the accuracy of recognition. Chinese handwritings cannot be converted into encoded texts until extracted and recognized correctly. Extracted handwritings may contain wrong language types, symbols, words, and word pairs. The conventional approach is based on context to adaptively correct theses errors. However, each writing character extraction candidates are fully visualized in bounding boxes, the overlaps of which bring more cognitive burden. Furthermore, the operation gesture needs to be accurate to stroke-level in convention that reduces the efficiency of correction. Therefore, an improved approach of error-correcting is proposed that an adaptive visualization as correcting reference and gesture analysis are taken into consideration. Experiments using real-life Chinese handwritings are conducted and compared the proposed approach with others. Experimental results demonstrate that the proposed approach is effective and robust.

Citation Download Citation

Hao Bai "Improved error-correcting from extracted handwritings in Chinese", Proc. SPIE 11913, Sixth International Workshop on Pattern Recognition, 119130D (6 August 2021); https://doi.org/10.1117/12.2604703

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KEYWORDS

Visualization

Data corrections

Detection and tracking algorithms

Error analysis

Gesture recognition

Human-computer interaction

Quantitative analysis

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