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Using a circular grid for offline handwritten character recognition

机译:使用圆形网格进行离线手写字符识别

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Offline handwritten recognition is more challenging as indicated by the recognition technologies. This study demonstrates significantly higher rates recognition when compared with other comparable studies. In this paper, we present a circular grid zoning method applied on Polar transformation recognition system. It compares the circular grid zoning (CGZ) and standard zoning (SZ) feature extraction method on Polar and Cartesian coordinate system. We report recognition rates of 92.3%, which are considerably higher than previous studies of zoning based Polar transformation system (86.6%) and zoning based Cartesian recognition system (80.6%). Based on the finding, we propose that our circular grid zoning based Polar transformation system may provide improved classification rates for complex offline handwritten recognition.
机译:如识别技术所示,离线手写识别更具挑战性。与其他可比研究相比,该研究显示出更高的识别率。在本文中,我们提出了一种应用于Polar变换识别系统的圆形网格分区方法。它在极坐标和笛卡尔坐标系上比较了圆形网格分区(CGZ)和标准分区(SZ)特征提取方法。我们报告的识别率为92.3%,大大高于以前基于分区的Polar转换系统(86.6%)和基于分区的笛卡尔识别系统(80.6%)的研究。基于这一发现,我们建议基于圆形网格分区的Polar转换系统可以为复杂的离线手写识别提供更高的分类率。

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