NDLI: Improving content-based image retrieval with compact global and local multi-features

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Improving content-based image retrieval with compact global and local multi-features

Content Provider	Springer Nature Link
Author	Ramzan, Naeem Amira, Abbes Jaber, Tareq Alzu’bi, Ahmad
Copyright Year	2016
Abstract	The accuracy of content-based image retrieval (CBIR) systems is significantly affected by the discriminatory power of image features and distance measures. This paper performs an investigation towards finding the best local and global features and distance measures for content-based image retrieval. It provides insights into the trade-offs regarding computational costs, memory utilization and accuracy on several standard datasets which include MIRFLICKR, Corel, Holidays and ZuBuD. First, low-dimensional global and local features are extracted individually to generate a bank of small image features. Second, multilevel descriptor forms are utilized to produce highly discriminative image representations based on multi-features aggregation scheme. The relationship is highlighted between features (local and global) and other retrieval factors such as quantization approaches, visual codebooks, distance measures, vectorization methods, memory and retrieval speed. The resulting composite image representations are compact, i.e., only 32–64 vector dimension and 32–128 codebook size, and preserve high discriminative levels which further boost the retrieval accuracy and performance. The experimental results show that the presented multi-features image representations are efficient and outperform many competitive methods of the state-of-the-art.
Starting Page	237
Ending Page	253
Page Count	17
File Format	PDF
ISSN	21926611
Journal	International Journal of Multimedia Information Retrieval
Volume Number	5
Issue Number	4
e-ISSN	2192662X
Language	English
Publisher	Springer London
Publisher Date	2016-09-27
Publisher Place	London
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Information Systems Applications (incl.Internet) Local detectors Principle component analysis Information Storage and Retrieval Data Mining and Knowledge Discovery Image Processing and Computer Vision Computer Science Similarity matching Compact quantization Content-based image retrieval Multimedia Information Systems Multi-feature analysis
Content Type	Text
Resource Type	Article
Subject	Library and Information Sciences Information Systems Media Technology

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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
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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
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9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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