Automatic Image and Video Tagging Survey

Authors

  • Suha Dh. Athab Department of Computer Science, University of Technology, Baghdad, Iraq https://orcid.org/0000-0001-6666-4916
  • Abdulamir Abdullah Karim Department of Computer Science, University of Technology, Baghdad, Iraq

DOI:

https://doi.org/10.24996/ijs.2023.64.9.44

Keywords:

Social media, Image tagging, Video tagging

Abstract

     Marking content with descriptive terms that depict the image content is called “tagging,” which is a well-known method to organize content for future navigation, filtering, or searching. Manually tagging video or image content is a time-consuming and expensive process. Accordingly, the tags supplied by humans are often noisy, incomplete, subjective, and inadequate. Automatic Image Tagging can spontaneously assign semantic keywords according to the visual information of images, thereby allowing images to be retrieved, organized, and managed by tag. This paper presents a survey and analysis of the state-of-the-art approaches for the automatic tagging of video and image data. The analysis in this paper covered the publications on tagging in Scopus and the Web of Science databases from 2008 to 2022.

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Published

2023-09-30

Issue

Section

Computer Science

How to Cite

Automatic Image and Video Tagging Survey. (2023). Iraqi Journal of Science, 64(9), 4865-4875. https://doi.org/10.24996/ijs.2023.64.9.44

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