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Proceedings Paper

ImageSeeker: a content-based image retrieval system
Author(s): Alaa Tawfik; HebatAllah Fouad; Reem Megahed; Samar Mohamed; Elsayed Hemayed
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Paper Abstract

In many areas of commerce, government, academia, and medicine, large collections of digital images are being used. Usually, the only way of searching these collections is by their name, or by browsing which is unpractical for large number of images. ImageSeeker aims at providing an improved technique to enhance image searching. It focuses on extracting visual contents from images and annotating them; it is based on the concept of CBIR (Content Based Image Retrieval) to retrieve the contents of the image based on what it has learnt during past trainings. When a user requests an image for a certain object, all images containing the same object will show up. ImageSeeker maintains high accuracy in finding matching results to the user's query. The system was tested on images containing natural scenes, specifically, see, sand, grass, clouds and sky.

Paper Details

Date Published: 19 January 2009
PDF: 11 pages
Proc. SPIE 7255, Multimedia Content Access: Algorithms and Systems III, 725507 (19 January 2009); doi: 10.1117/12.810090
Show Author Affiliations
Alaa Tawfik, Cairo Univ. (Egypt)
HebatAllah Fouad, Cairo Univ. (Egypt)
Reem Megahed, Cairo Univ. (Egypt)
Samar Mohamed, Cairo Univ. (Egypt)
Elsayed Hemayed, Cairo Univ. (Egypt)


Published in SPIE Proceedings Vol. 7255:
Multimedia Content Access: Algorithms and Systems III
Raimondo Schettini; Ramesh C. Jain; Simone Santini, Editor(s)

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