Researchers in China have recognized that optical character recognition (OCR) has matured and can identify and extract information from documents that use standard writing styles. Now a team has developed an algorithm that can, with fine granularity, extract information from what might be loosely terms graffiti, convoluted handwriting that might even be indecipherable to a human reader.
Jiashuang Xu and Zhangjie Fu of the Computer and Software College at Nanjing University of Information Science and Technology, and Xingyue Du of the School of Humanities and Social Sciences at Xi'an Polytechnic University, provide details of their approach in "Graffiti-Writing Recognition With Fine-Grained Information," published in the International Journal of Computational Science and Engineering.
So far the team has trained their system to recognize 26 letters of the English alphabet with 85.96 percent accuracy and are now working on extending and improving the technology. The system utilizes a motion-detection approach rather than requiring touch input and so could be adapted for non-screen input devices such as wearables, where one might gesture to a device embedded in clothing, for instance.
From Tech Xplore
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