Informing Content- and Concept-Based Image Indexing and Retrieval through a Study of Image Description

Public Deposited
Analytics

Downloadable Content

Download PDF
Request Version for Screen Reader
Last Modified
  • February 28, 2019
Creator
  • Kennedy, Marie R.
    • Affiliation: School of Information and Library Science
Abstract
  • This research reports on a Web survey of visual resource experts. The research uses the data supplied by the experts to discuss if content-and concept-based image indexing and retrieval approaches may be improved by examining features relevant to both. Image descriptions were gathered from image professionals via a Web survey. The descriptions were analyzed to test whether color images evoke a denser textual description than grayscale images, and whether there is any significant variation in the words used to describe them. Analyses of data resulting from the survey of image description indicate that image professionals describe images with high-level concepts rather than low-level features, and that color does not affect the number or type of words used in their descriptions. This work may prompt future research with other building blocks of the systems in order to better integrate the research done by computer and library scientists in this area.
Date of publication
Subject
DOI
Resource type
Rights statement
  • In Copyright
Advisor
  • Greenberg, Jane
Degree granting institution
  • University of North Carolina at Chapel Hill
Language
Extent
  • 40 p.
Access right
  • Open access
Date uploaded
  • December 10, 2010

Relations

Parents:

This work has no parents.

Items

Thumbnail Title Date Uploaded Visibility Actions
file details Informing Content- and Concept-Based Image Indexing and Retrieval through a Study of Image Description 2019-05-13 Public Download