NDLI: Adaptive clustering based segmentation for image classification

Content Provider	IEEE Xplore Digital Library
Author	Al-Jubouri, H. Hongbo Du Sellahewa, H.
Copyright Year	2013
Description	Author affiliation: Dept. of Appl. Comput., Univ. of Buckingham, Buckingham, UK (Al-Jubouri, H.; Hongbo Du; Sellahewa, H.)
Abstract	Image segmentation based on clustering low-level image features such as colour and texture, has been successfully employed in image classification and content-based image retrieval. In segmentation based image classification, the role of clustering to segment an image into its relevant constituents that represent image visual content as well as its semantic content. However, image content can vary from having a simple foreground object on a regular background to having multiple objects of different sizes, shapes, colour and texture in complex background scenes. This makes automatic image classification a challenging task. This paper evaluates three adaptive clustering algorithms of different categories, i.e., partition-based, model-based, and density-based in segmenting local colour and texture features for image classification. Experiments are conducted on the publicly available WANG database. The results show that the adaptive EM/GMM algorithm outperforms the adaptive k-means and mean shift algorithms.
Starting Page	128
Ending Page	133
File Size	1039064
Page Count	6
File Format	PDF
ISBN	9781479903832
DOI	10.1109/CEEC.2013.6659459
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-09-17
Publisher Place	UK
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	K-means Classification algorithms Partitioning algorithms Clustering Based Image Retrieval Image segmentation EM/GMM Mean shift Image color analysis DCT Clustering algorithms Content Classification Feature extraction Image classification
Content Type	Text
Resource Type	Article

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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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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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