支持深度学习的混合系统用于准确识别海图像中的文本
Keke Zhang1, Mingyu Guan2, Chao Wu3
1College of Artificial Intelligence and Big Data, Chongqing Polytechnic University of Electronic Technology, Chongqing, China.
Frontiers in big data
|January 30, 2026
概括
本研究提出了一种混合模型,用于识别中国印章上的文字,克服了背景噪音和最小特征等挑战. 这种新的方法显著提高了中国印章文本识别的准确性.
科学领域:
- 计算机视觉 计算机视觉
- 光学字符识别 (OCR) 是一个技术.
- 人工智能的人工智能
背景情况:
- 中国的印章对于中国的法律文件认证至关重要.
- 由于背景文字,噪音和最小的特征,很难识别印章上的文本.
研究的目的:
- 为准确的中国印章文本识别开发混合模型.
- 为了应对噪音和复杂的海图像所带来的挑战.
主要方法:
- 这是一个混合模型,集成了预处理,位置校正的深度学习,循环文本解封和OCR.
- 基于颜色的背景删除,新的图像消除,基于合成数据集的基于深度学习的角度预测,以及用于文本解封的极坐标转换.
主要成果:
- 提出的方法有效地提高了中国印章文本识别的准确性.
- 混合动力车型表现出对抗噪音和复杂背景的强度提高.
结论:
- 开发的混合型号为中国印章文本识别提供了强大的解决方案.
- 集成先进的预处理和深度学习技术显著提高了识别性能.
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