Convolutional Neural Network for Colorization of Black and White Photos

  • Siti Ummi Masruroh UIN Syarif Hidayatullah, Jakarta, Indonesia
  • Andrew Fiade UIN Syarif Hidayatullah, Jakarta, Indonesia
  • Muhammad Ikhsan Tanggok UIN Syarif Hidayatullah, Jakarta, Indonesia
  • Rizka Amalia Putri UIN Syarif Hidayatullah, Jakarta, Indonesia
  • Luigi Ajeng Pratiwi Advanced Institute of Science & Technology, Daejeon, South Korea
Keywords: Convolutional Neural Network, Colorization, Deep Learning, Photos Colorization


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.


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How to Cite
Masruroh, S., Fiade, A., Tanggok, M., Putri, R., & Pratiwi, L. (2023). Convolutional Neural Network for Colorization of Black and White Photos. MATRIK : Jurnal Manajemen, Teknik Informatika Dan Rekayasa Komputer, 22(2), 393-404.

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