• Satyam Akunuri
• A. Chandu Naik
• B.Rajendra Prasad

The central problem of Automatic Image Colorization revolves around our ability to come up with a clear way of computing the Colored Image from the given Black and white Image. So, there won’t be any accurate answer for the Black and White Images if we give wide range of Black and White images. So, many algorithms came up to solve this problem. There are solutions to this problem through manually colorizing each and every pixel of the image. By doing manually, we can maximum try to make the Black and White Image to a good looking colored Image. But it takes very long time. Before deep learning arrived at the scene, researchers had been handcrafting methods to colorize each pixel of the Image. Even in today's research of style transfer using deep learning there are high impact papers proposing new ways of using a neural network to Colorize the given Black and White Image. This system can be used as an application for colorizing the user given Black and White images.

Image Colorization, Tensor Flow, Convolutional Neural Networks, Grey Scale images

"A Novel Approach for Automatic Image Colorization", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.4, Issue 11, page no.535-537, November 2017, Available :http://www.jetir.org/papers/JETIR1808833.pdf

"A Novel Approach for Automatic Image Colorization", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.4, Issue 11, page no. pp535-537, November 2017, Available at : http://www.jetir.org/papers/JETIR1808833.pdf