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A CCD based machine vision system for real-time text detection

机译:基于CCD的实时文本检测机器视觉系统

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摘要

Text detection and recognition is a hot topic in computer vision, which is considered to be the further development of the traditional optical character recognition (OCR) technology. With the rapid development of machine vision system and the wide application of deep learning algorithms, text recognition has achieved excellent performance. In contrast, detecting text block from complex natural scenes is still a challenging task. At present, many advanced natural scene text detection algorithms have been proposed, but most of them run slow due to the complexity of the detection pipeline and cannot be applied to industrial scenes. In this paper, we proposed a CCD based machine vision system for real-time text detection in invoice images. In this system, we applied optimizations from several aspects including the optical system, the hardware architecture, and the deep learning algorithm to improve the speed performance of the machine vision system. The experimental data confirms that the optimization methods can significantly improve the running speed of the machine vision system and make it meeting the real-time text detection requirements in industrial scenarios.
机译:文本检测和识别是计算机愿景中的热门话题,被认为是传统光学字符识别(OCR)技术的进一步发展。随着机器视觉系统的快速发展和深度学习算法的广泛应用,文本识别取得了良好的性能。相比之下,从复杂的自然场景中检测文本块仍然是一个具有挑战性的任务。目前,已经提出了许多先进的自然场景文本检测算法,但由于检测管道的复杂性,它们中的大部分都是缓慢的,并且不能应用于工业场景。在本文中,我们提出了一种基于CCD的机器视觉系统,用于在发票图像中的实时文本检测。在该系统中,我们从包括光学系统,硬件架构和深度学习算法的多个方面应用了优化,以提高机器视觉系统的速度性能。实验数据确认优化方法可以显着提高机器视觉系统的运行速度,使其在工业方案中满足实时文本检测要求。

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