Automatic Image Colorization using Deep Learning
Abhishek Pandey1, Rohit Sahay2, C. Jayavarthini3
1Abhishek Pandey, Department of Computer Science and Engineering, SRM Institute of Science and Technology, Kattankulathur, India.
2Rohit Sahay, Department of Computer Science and Engineering, SRM Institute of Science and Technology, Kattankulathur, India.
3Mrs. C. Jayavarthini, Faculty of Computer Science and Engineering, SRM Institute of Science and Technology, Kattankulathur, India.
Manuscript received on February 10, 2020. | Revised Manuscript received on February 20, 2020. | Manuscript published on March 30, 2020. | PP: 1592-1995 | Volume-8 Issue-6, March 2020. | Retrieval Number: F7719038620/2020©BEIESP | DOI: 10.35940/ijrte.F7719.038620
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Image colorization is a fascinating topic and has become an area of research in the recent years. In this project, we are going to colorize black and white images with the help of Deep Learning techniques. Some previous approaches required human involvement or resulted in the development of desaturated images. We are building a Deep Convolutional Neural Network (CNN) which will be trained on over a million images. The output generated by the model is fully dependent on the images it has been trained from and requires no human help. The images are taken from different sources like ResNet, Reddit, etc. The model will include many hidden layers to make the output more accurate. This will be a fully automatic model and will produce images with accurate colors and contrast. Finally, the goal of this project is to produce realistic and color accurate images that can easily fool the viewer. The viewer wouldn’t be able to differentiate between the photo which the model produced and the real photo. Our project has wide practical applications like historical image/video restoration, image enhancement for better interpretability, frame by frame colorization of black and white documentaries, etc.
Keywords: CNN, CSV, DL, ML, GAN.
Scope of the Article: Deep Learning.