NDLI: Scheme for unsupervised colour–texture image segmentation using neutrosophic set and non-subsampled contourlet transform

Content Provider	IET Digital Library
Author	Heshmati, Abed Gholami, Maryam Rashno, Abdolreza
Abstract	The process of partitioning an image into some different meaningful regions with the homogeneous characteristics is called the image segmentation which is a crucial task in image analysis. This study presents an efficient scheme for unsupervised colour–texture image segmentation using neutrosophic set (NS) and non-subsampled contourlet transform (NSCT). First, the image colour and texture information are extracted via CIE Luv colour space model and NSCT, respectively. Then, the extracted colour and texture information are transformed into the NS domain efficiently by the authors’ proposed approach. In the NS-based image segmentation, the indeterminacy assessment of the images in the NS domain is notified by the entropy concept. The lower quantity of indeterminacy in the NS domain, the higher confidence and easier segmentation could be achieved. Therefore, to achieve a better segmentation result, an appropriate indeterminacy reduction operation is proposed. Finally, the K-means clustering algorithm is applied to perform the image segmentation in which the cluster number K is determined by the cluster validity analysis. To show the effectiveness of their proposed method, its performance is compared with that of the state-of-the-art methods. The experimental results reveal that their segmentation scheme outperforms the other methods for the Berkeley dataset.
Starting Page	464
Ending Page	473
Page Count	10
ISSN	17519659
Volume Number	10
e-ISSN	17519667
Issue Number	Issue 6, Jun (2016)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-ipr/10/6
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-ipr.2015.0738
Journal	IET Image Processing
Publisher Date	2016-06-01
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Berkeley Dataset CIE Luv Colour Space Model Cluster Validity Analysis Combinatorial Mathematics Computer Vision And Image Processing Technique Data Handling Technique Entropy Entropy Concept Homogeneous Characteristic Image Analysis Image Colour Analysis Image Indeterminacy Assessment Image Partitioning Image Segmentation Image Texture Indeterminacy Reduction Operation K-means Clustering Algorithm Knowledge Engineering Technique Neutrosophic Set Nonsubsampled Contourlet Transform NS-based Image Segmentation NSCT Optical, Image And Video Signal Processing Pattern Clustering Set Theory Unsupervised Colour–texture Image Segmentation Unsupervised Learning
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering 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

Colour image encryption technique using differential evolution in non-subsampled contourlet transform domain

Image fusion method based on simultaneous sparse representation with non-subsampled contourlet transform

Hybrid image denoising method based on non-subsampled contourlet transform and bandelet transform

Texture-based image segmentation using neutrosophic clustering

Efficient clustering approach for adaptive unsupervised colour image segmentation

Despeckling SAR images based on a new probabilistic model in nonsubsampled contourlet transform domain

A Novel Unsupervised Two-Stage Technique in Color Image Segmentation

Human perception-based image segmentation using optimising of colour quantisation

An Affinity-Based Algorithm in Nonsubsampled Contourlet Transform Domain: Application to Synthetic Aperture Radar Image Denoising

Scheme for unsupervised colour–texture image segmentation using neutrosophic set and non-subsampled contourlet transform

Similar Documents

Colour image encryption technique using differential evolution in non-subsampled contourlet transform domain

Image fusion method based on simultaneous sparse representation with non-subsampled contourlet transform

Hybrid image denoising method based on non-subsampled contourlet transform and bandelet transform

Texture-based image segmentation using neutrosophic clustering

Efficient clustering approach for adaptive unsupervised colour image segmentation

Despeckling SAR images based on a new probabilistic model in nonsubsampled contourlet transform domain

A Novel Unsupervised Two-Stage Technique in Color Image Segmentation

Human perception-based image segmentation using optimising of colour quantisation

An Affinity-Based Algorithm in Nonsubsampled Contourlet Transform Domain: Application to Synthetic Aperture Radar Image Denoising

Scheme for unsupervised colour–texture image segmentation using neutrosophic set and non-subsampled contourlet transform