Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/40372
Full metadata record
DC FieldValueLanguage
dc.contributor.authorLe, Khanh Vinh.-
dc.date.accessioned2010-06-15T03:27:29Z-
dc.date.available2010-06-15T03:27:29Z-
dc.date.copyright2010en_US
dc.date.issued2010-
dc.identifier.urihttp://hdl.handle.net/10356/40372-
dc.description.abstractThe use of tagging is one of the most important and popular features of the second generation web development and design (Web 2.0). The key highlight of using a tag is to give a keyword or a term to a piece of information to describe the contents of object for images. With these tags organized, users can efficiently browse and search the information they may require using a search engine. However, tagging is often very time consuming and tedious to do especially on images. With over billions of images hosted on the internet and they are neither tagged nor described. These images cannot be searched or be used to find similar information as there is no metadata bind to it. And therefore information in the image could not be used effectively. As there is a strong growing number of images uploaded every day, this makes it ideal to develop a automated image tagging system. This system must be able to tag the images fairly accurately and efficiently to generate the result at real time. The proposed system with a prototype developed in my project makes use of the color histogram for a few customized comparison methods and the result will be discussed. This report highlights a process developed for image tagging. And the focus of the report is on the new color histogram module which is the main image processing part. The design, implementation and simulation result will be discussed in this report.en_US
dc.format.extent78 p.en_US
dc.language.isoenen_US
dc.rightsNanyang Technological University-
dc.subjectDRNTU::Engineering::Electrical and electronic engineering::Computer hardware, software and systemsen_US
dc.titleAuto tagging on smart search interneten_US
dc.typeFinal Year Project (FYP)en_US
dc.contributor.supervisorChen Lihuien_US
dc.contributor.schoolSchool of Electrical and Electronic Engineeringen_US
dc.description.degreeBachelor of Engineeringen_US
dc.contributor.researchCentre for Signal Processingen_US
item.grantfulltextrestricted-
item.fulltextWith Fulltext-
Appears in Collections:EEE Student Reports (FYP/IA/PA/PI)
Files in This Item:
File Description SizeFormat 
Final.pdf
  Restricted Access
3.79 MBAdobe PDFView/Open

Page view(s)

219
Updated on Nov 28, 2020

Download(s) 1

4
Updated on Nov 28, 2020

Google ScholarTM

Check

Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.