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Multi-operator combination for character segmentation in complex background

机译:多操作员组合用于复杂背景中的字符分割

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Automatic character segmentation is the first most fundamental and crucial step for the Optical Character Recognition (OCR) system. Though there have been a lot mature commercial OCR systems for controlled environment, the techniques of OCR are not as popular as expected for the complex uncontrolled environment. The bottleneck is character segmentation from noisy background. In this paper, we propose a multi-operator combined character segmentation algorithm to partition the characters from complex background. To handle the uncontrolled lighting condition, we propose a localized Canny operator for pre-edge detection and refine it with the Compass operator to promote the accuracy of edge detection under complex background. The proposed algorithm involves the advantage of the localized Canny operator in speed and the advantage of Compass Operator in accuracy. By comparing with other algorithms and analyzing the performance of the proposed algorithm, it can be concluded that our algorithm can achieve a better result of character segmentation in complex scenarios.
机译:自动字符分割是光学字符识别(OCR)系统的第一个最基本也是最关键的步骤。尽管已经有很多成熟的用于受控环境的商业OCR系统,但是OCR技术并不像预期的那样在复杂的不受控制的环境中流行。瓶颈是来自嘈杂背景的字符分割。在本文中,我们提出了一种多算子组合字符分割算法,用于对复杂背景下的字符进行分割。为了处理不受控制的照明条件,我们建议使用本地化的Canny算子进行边缘检测,并使用Compass算子进行完善,以提高复杂背景下边缘检测的准确性。所提算法具有局部Canny算子在速度上的优势和Compass算子在精度上的优势。通过与其他算法进行比较并分析该算法的性能,可以得出结论,该算法在复杂场景下可以达到较好的字符分割效果。

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