NDLI: Image clustering using exponential discriminant analysis

Content Provider	IET Digital Library
Author	Ahmed, Nasir
Abstract	Local learning based image clustering models are usually employed to deal with images sampled from the non-linear manifold. Recently, linear discriminant analysis (LDA) based various clustering models were proposed. However, in these clustering models, regularisation parameter was added to handle the small-sample-size (SSS) problem of LDA for high-dimensional image data. Owing to this, the authors had to tune a number of clustering parameters for optimal clustering performance in existing local learning based clustering approaches. In this study, the less-parameterised local learning based image clustering model is proposed. The proposed local exponential discriminant clustering (LEDC) model is based on exponential discriminant analysis (EDA). In the LEDC model, local scatter matrices are projected in the exponential domain in order to handle the SSS problem of LDA without adding regularisation parameter. In the proposed LEDC model, k-nearest neighbours are the only clustering parameter as compared with existing local learning based clustering approaches such as normalised cut, spectral embedded clustering and local discriminant model and global integration (LDMGI). Experimental results on twelve benchmark image datasets show that the LEDC model achieved a comparable clustering performance as that of the near competitor LDMGI model. Clustering performance is comparable because no discriminant information of LDA is lost in EDA. The authors concluded that the proposed LEDC clustering model is less-parameterised with a comparable clustering performance as that of existing state-of-the-art local learning based clustering approaches.
Starting Page	1
Ending Page	12
Page Count	12
ISSN	17519632
Volume Number	9
e-ISSN	17519640
Issue Number	Issue 1, Feb (2015)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-cvi/9/1
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-cvi.2013.0144
Journal	IET Computer Vision
Publisher Date	2014-06-19
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Benchmark Image Datasets Clustering Parameter Computer Vision And Image Processing Technique Data Handling Technique Exponential Discriminant Analysis Exponential Domain High-dimensional Image Data Image Sampling Integration K-nearest Neighbours Knowledge Engineering Technique LDMGI Model Learning in AI LEDC Model Less-parameterised Local Learning Based Image Clustering Model Local Discriminant Model And Global Integration Local Exponential Discriminant Clustering Model Mathematical Analysis Nonlinear Manifold Optical, Image And Video Signal Processing Optimal Clustering Performance Pattern Clustering SSS Problem Statistics
Content Type	Text
Resource Type	Article
Subject	Computer Vision and Pattern Recognition Software

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

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