Prior to the availability of digital cameras, the solar observational images are typically recorded on films, and the information such as date and time were stamped in the same frames on film. It is significant to extract the time stamp information on the film so that the researchers can efficiently use the image data. This paper introduces an intelligent method for extracting time stamp information, namely, the convolutional neural network (CNN), which is an algorithm in deep learning of multilayer neural network structures and can identify time stamp character in the scanned solar images. We carry out the time stamp decoding for the digitized data from the National Solar Observatory from 1963 to 2003. The experimental results show that the method is accurate and quick for this application. We finish the time stamp information extraction for more than 7 million images with the accuracy of 98%.

中文翻译：

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胶片太阳扫描图像中时间戳字符的智能识别

在提供数码相机之前，通常将太阳观测图像记录在胶片上，并将日期和时间等信息盖在胶片上的同一帧中。提取影片上的时间戳信息非常重要，这样研究人员才能有效地使用图像数据。本文介绍了一种智能的时间戳信息提取方法，即卷积神经网络（CNN），它是一种深度学习多层神经网络结构的算法，可以识别扫描的太阳图像中的时间戳特征。从1963年到2003年，我们对国家太阳台的数字化数据进行了时间戳解码。实验结果表明，该方法准确，快速。