Convolutional Neural Network for Colorization of Black and White Photos

S. Masruroh, Andrew Fiade, M. I. Tanggok, Rizka Amalia Putri, Luigi Ajeng Pratiwi
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引用次数: 1

Abstract

People today are very fond of capturing moments by taking pictures. Various photo functions are used to document all forms of information that you want to store. In photos with digital images that have black and white, the information obtained is less than optimal, so an image processing process is needed to get color photos. Based on this, the author wants to change photos from black and white to color photos. The method used in this research is Convolutional Neural Network (CNN). This study uses Atlas 200 DK hardware and Ascend 310 processor. The data used in this study are 32 black and white photos in .jpg format as training data and perform 6 experimental scenarios with different numbers of black and white photos in each experiment. The total black and white photos used to experiment were 81 photos. The results obtained are models that successfully perform processing in the form of color photos with the appropriate color results in predicting the possible color of the object in each pixel in the photo. Based on this research, the trend of artificial intelligence can be implemented in changing the color of photos according to color predictions.
卷积神经网络用于黑白照片的着色
今天的人们非常喜欢通过拍照来捕捉瞬间。各种照片函数用于记录您想要存储的所有形式的信息。在带有黑白图像的数字照片中,获得的信息不是最优的,因此需要一个图像处理过程来获得彩色照片。基于此,笔者想把照片从黑白换成彩色。本研究使用的方法是卷积神经网络(CNN)。本研究采用Atlas 200 DK硬件和Ascend 310处理器。本研究使用的数据为。jpg格式的32张黑白照片作为训练数据,并在每个实验中使用不同数量的黑白照片进行6个实验场景。用于实验的黑白照片共81张。得到的结果是成功地以彩色照片的形式进行处理的模型,具有适当的颜色结果,可以预测照片中每个像素中物体的可能颜色。基于此研究,可以实现人工智能的趋势,根据颜色预测来改变照片的颜色。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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