Image Colorizer using OpenCv and Convolutional Neural Networks
Parthib Ranjan Ray
, Akshay Narisetti , Dr.R.Renuka Devi
Image Colorization, Convolution neural networks, Feature extractor, Decoder
Given a grayscale photograph or video as input, this
project attempts to create a plausible color version of the
photograph. This problem is clearly underconstrained, so
previous approaches have either relied on significant user
interaction or resulted in desaturated colorizations. We propose
a fully automatic approach that produces vibrant and realistic
colorizations. We embrace the underlying uncertainty of the
problem by posing it as a classification task and use
class-rebalancing at training time to increase the diversity of
colors in the result. Colorizing images has a significant impact
in different fields, such as photography of astronomical objects,
the visuals of electronic microscopes, and CCTV surveillance
systems. Using Deep Learning algorithms, we can build an
automated system for analyzing color grayscale images.
"Image Colorizer using OpenCv and Convolutional Neural Networks", IJNRD - INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT (www.IJNRD.org), ISSN:2456-4184, Vol.8, Issue 3, page no.a816-a819, March-2023, Available :https://ijnrd.org/papers/IJNRD2303086.pdf
Volume 8
Issue 3,
March-2023
Pages : a816-a819
Paper Reg. ID: IJNRD_188216
Published Paper Id: IJNRD2303086
Downloads: 000118854
Research Area: Computer Engineering
Country: Nagpur, Maharashtra, India
ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
Publisher: IJNRD (IJ Publication) Janvi Wave
