首页> 外文期刊>International Journal of Computers & Applications >ALGORITHMS TO GENERATE PARTIALLY DAMAGED CHARACTERS AND READABILITY STUDY FOR OCR READERS IN SEMICONDUCTOR MANUFACTURING
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ALGORITHMS TO GENERATE PARTIALLY DAMAGED CHARACTERS AND READABILITY STUDY FOR OCR READERS IN SEMICONDUCTOR MANUFACTURING

机译:半导体制造中OCR读取器产生部分损坏特征的算法和可读性研究

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摘要

Ever since the character strings on silicon wafers were read using QCR (Optical Character Recognition) cameras, there has been a problem with damaged characters. This problem is due to reflection from the light source or physical damage of the characters themselves. There are obvious types of damage that occur frequently on many of the bitmaps that the OCR camera reads. With these types, one can test them to find the most damaging types for each particular character. However, currently there is no known research that systematically determines the worst damages or limits of damage to characters for specific OCR methods such as template matching or neural network algorithms This article presents algorithms for testing common forms of damages on template-matching optical readers reading strings on silicon wafers. It also displays results from combining a simple neural network and the algorithms. The results on readability are critical for the development of robust OCR systems.
机译:自从使用QCR(光学字符识别)相机读取硅片上的字符串以来,就存在字符损坏的问题。该问题是由于光源的反射或字符本身的物理损坏造成的。 OCR相机读取的许多位图上经常发生明显的损坏类型。使用这些类型,可以测试它们以找到每个特定字符最具破坏性的类型。但是,目前还没有已知的研究能够系统地确定针对特定OCR方法(例如模板匹配或神经网络算法)的字符的最严重损坏或损坏极限。本文介绍了用于在与模板匹配的光学读取器上读取字符串的常见损坏形式的算法在硅晶圆上。它还显示了结合简单神经网络和算法的结果。可读性的结果对于开发强大的OCR系统至关重要。

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