Query image retrieval using similarity measure classifier
Author
Source
Issue
Vol. 2013, Issue 31 للعلوم التطبيقية (30 Sep. 2013), pp.151-156, 6 p.
Publisher
Publication Date
2013-09-30
Country of Publication
Yemen
No. of Pages
6
Main Subjects
Information Technology and Computer Science
Abstract EN
Query by image content (QBIC) is the application of computer vision to the image retrieval problem, that is, the problem of searching for digital images in large databases.
Without the ability to examine image content, searches must rely on metadata such as captions or keywords, which may be laborious or expensive to produce.
In this paper, we work on specifi image to retrieve images that are similar in shape, texture and/or color to an image using some similarity measures.
We show statistical results of the different techniques that we use in different stages of our QBIC system.
We tested five different Sigma in GRNN Neural Network and five different image enhancement techniques.
Also, we have six different gradient masks, so we specify which enhancement technique works better with which masks, to retrieve the image in high value of similar measure.
American Psychological Association (APA)
al-Zurqa, Insaf A.. 2013. Query image retrieval using similarity measure classifier. al-Bāḥith al-Jāmiʻī،Vol. 2013, no. 31 للعلوم التطبيقية, pp.151-156.
https://search.emarefa.net/detail/BIM-958708
Modern Language Association (MLA)
al-Zurqa, Insaf A.. Query image retrieval using similarity measure classifier. al-Bāḥith al-Jāmiʻī No. 31 للعلوم التطبيقية (Jul. / Sep. 2013), pp.151-156.
https://search.emarefa.net/detail/BIM-958708
American Medical Association (AMA)
al-Zurqa, Insaf A.. Query image retrieval using similarity measure classifier. al-Bāḥith al-Jāmiʻī. 2013. Vol. 2013, no. 31 للعلوم التطبيقية, pp.151-156.
https://search.emarefa.net/detail/BIM-958708
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references : p. 155-156
Record ID
BIM-958708