Cartoonizer: Convert Images and Videos to Cartoon-Style Images and Videos

Authors

  • S. Rajatha Student, Department of Information Science and Engineering, Srinivas Institute of Technology, Mangaluru, India
  • Anusha Shrikant Makkigadde Student, Department of Information Science and Engineering, Srinivas Institute of Technology, Mangaluru, India
  • Neha L. Kanchan Student, Department of Information Science and Engineering, Srinivas Institute of Technology, Mangaluru, India
  • Sapna Student, Department of Information Science and Engineering, Srinivas Institute of Technology, Mangaluru, India
  • K. Janardhana Bhat Associate Professor, Department of Information Science and Engineering, Srinivas Institute of Technology, Mangaluru, India

Keywords:

Animation, Generative Adversarial Network (GAN), Image processing, Video processing

Abstract

The process of converting real-life high-quality pictures and videos into practical cartoon images and videos is known as cartoonization. The saved model decomposes uploaded images and videos into three different cartoon depictions as surface representation, structure representation, texture representation, which further instructs the network optimization to generate cartoon image. It helps to sleek the image, filter the qualities, transforming it to sketches, and translating the output from a domain to another. The extracted outputs are fed to a Generative Neural Networks (GAN) framework, which helps to improve our problem making the solution more flexible and varied, where GAN stands for Generative Adversarial Network is used to transform uploaded images (snapshots) to the finest cartooned image. Using the loss function and its two types named as Adversarial loss and Content Loss, we gained a flexible as well as a clear edge defined images.

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Published

23-07-2021

How to Cite

[1]
S. Rajatha, A. S. Makkigadde, N. L. Kanchan, Sapna, and K. J. Bhat, “Cartoonizer: Convert Images and Videos to Cartoon-Style Images and Videos”, IJRESM, vol. 4, no. 7, pp. 275–278, Jul. 2021.

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