In this research, we present a heuristic method for character recognition.
For this purpose, a sketch is constructed from the image that contains the
character to be recognized. This sketch contains the most important pixels of
image that are representatives of original image. These points are the most
probable points in pixel-by-pixel matching of image that adapt to target image.
Furthermore, a technique called gravity shifting is utilized for taking over
the problem of elongation of characters. The consequence of combining sketch
and gravity techniques leaded to a language free character recognition method.
This method can be implemented independently for real-time uses or in
combination of other classifiers as a feature extraction algorithm. Low
complexity and acceptable performance are the most impressive features of this
method that let it to be simply implemented in mobile and battery-limited
computing devices. Results show that in the best case 86% of accuracy is
obtained and in the worst case 28% of recognized characters are accurate.

本研究介绍了一种基于启发式方法的字符识别方法，利用草图和重力转移技术实现无语言限制的低复杂度字符识别，并可独立运用于实时目标检测中。在测试中，最高可达 86% 的识别率，最低为 28%。