NDLI: Image retrieval using Contourlet based interest points

Content Provider	IEEE Xplore Digital Library
Author	Hoang Ng-Duc Thuong Le-Tien Tuan Do-Hong Cao Bui-Thu Ty Ng-Xuan
Copyright Year	2010
Description	Author affiliation: Navy Institute Nha Trang, Vietnam (Ty Ng-Xuan) \|\| Broadcast Research and Application Center, Vietnam Television (VTV-BRAC), Vietnam (Hoang Ng-Duc) \|\| Ho Chi Minh City University of Technology, Vietnam (Thuong Le-Tien; Tuan Do-Hong) \|\| Ho Chi Minh City University of Industry, Vietnam (Cao Bui-Thu)
Abstract	In this work we present the method for image retrieval based on the Non-Subsampled Contourlet Transform (NSCT) and the Harris corner detector. The NTSC-based interest point detector is proposed by combination of NTSC and Harris corner detector called the Contourlet Harris detector. We also present the method how to extract the image features using this Contourlet Harris detector that is applied for image retrieval. Experiments are implemented on the WANG database aiming to compare retrieval effectiveness of proposed method to some methods have announced. Results demonstrate that the proposed method shows a quite improvement in the retrieval effectiveness.
Starting Page	93
Ending Page	96
File Size	1186460
Page Count	4
File Format	PDF
ISBN	9781424471652
e-ISBN	9781424471676
DOI	10.1109/ISSPA.2010.5605500
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-05-10
Publisher Place	Malaysia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Horses Presses Dinosaurs Buildings Detectors Contourlet Harris detector content-based image retrieval CBIR Non-Subsampled Contourlet Transform
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Interest points matching system based On Non-Subsampled Contourlet Transform

Non-subsampled contourlet texture image retrieval system utilizing three features

Texture Image Retrieval System Based on Non-Subsampled Contourlet and Generalized Gaussian Density Model

A new descriptor for image retrieval using Contourlet Co-Occurrence

Efficient content based image retrieval based on Semantic Object Detection

Contourlet Based Interest Points Detector

Local image representations using pruned salient points with applications to CBIR

A Novel Image Retrieval Technique Based on Salient Image Features

Interactive content-based texture image retrieval

Image retrieval using Contourlet based interest points

Similar Documents

Interest points matching system based On Non-Subsampled Contourlet Transform

Non-subsampled contourlet texture image retrieval system utilizing three features

Texture Image Retrieval System Based on Non-Subsampled Contourlet and Generalized Gaussian Density Model

A new descriptor for image retrieval using Contourlet Co-Occurrence

Efficient content based image retrieval based on Semantic Object Detection

Contourlet Based Interest Points Detector

Local image representations using pruned salient points with applications to CBIR

A Novel Image Retrieval Technique Based on Salient Image Features

Interactive content-based texture image retrieval

Image retrieval using Contourlet based interest points