Skip to main content
padlock icon - secure page this page is secure

Blind Identification Technology of Computer Generated Image Based on Texture Recognition

Buy Article:

$105.00 + tax (Refund Policy)

With the popularization of digital products and the promotion of image processing software, it provides a way to tamper with the image. Therefore, the identification of natural images and computer generated images has become the focus of scholars’ research. In this paper, a blind identification technique for computer generated images based on texture recognition was proposed, and the algorithm and process of the blind identification of computer generated images based on texture recognition was described. Finally, through the analysis of the experimental data, it was concluded that the characteristic dimension K1 of the differential excitation information was 5 the most suitable, and the Sobel gradient direction information characteristic dimension K2 was 9.
No Reference information available - sign in for access.
No Citation information available - sign in for access.
No Supplementary Data.
No Article Media
No Metrics

Keywords: Blind Identification; Blind Identification Technology; Computer Generated Image; Texture Recognition

Document Type: Research Article

Affiliations: School of Software Engineering, Beijing Jiaotong University, Beijing 100044, China

Publication date: 01 July 2017

More about this publication?
  • Journal of Computational and Theoretical Nanoscience is an international peer-reviewed journal with a wide-ranging coverage, consolidates research activities in all aspects of computational and theoretical nanoscience into a single reference source. This journal offers scientists and engineers peer-reviewed research papers in all aspects of computational and theoretical nanoscience and nanotechnology in chemistry, physics, materials science, engineering and biology to publish original full papers and timely state-of-the-art reviews and short communications encompassing the fundamental and applied research.
  • Editorial Board
  • Information for Authors
  • Submit a Paper
  • Subscribe to this Title
  • Terms & Conditions
  • Ingenta Connect is not responsible for the content or availability of external websites
  • Access Key
  • Free content
  • Partial Free content
  • New content
  • Open access content
  • Partial Open access content
  • Subscribed content
  • Partial Subscribed content
  • Free trial content
Cookie Policy
Cookie Policy
Ingenta Connect website makes use of cookies so as to keep track of data that you have filled in. I am Happy with this Find out more