A Student's t‐based density peaks clustering with superpixel segmentation (tDPCSS) method for image color clustering-Reference-Cited by-同舟云学术

A Student's t‐based density peaks clustering with superpixel segmentation (tDPCSS) method for image color clustering

Published:2020-02-20 Issue:4 Volume:45 Page:656-670
ISSN:0361-2317
Container-title:Color Research & Application
language:en
Short-container-title:Color Res Appl

Author:

Li Zhijiang¹,Zheng Yingping¹,Cao Liqin¹^ORCID,Jiao Lei²,Zhong Yanfei³,Zhang Caiyi¹

Affiliation:

1. School of Printing and Packaging Wuhan University Hubei China

2. Department of Information and Communication Technology University of Agder Grimstad Norway

3. State Key Laboratory of Information Engineering in Mapping, Surveying and Remote Sensing Wuhan University Hubei China

Funder

Fundamental Research Funds for the Central Universities

National Key Research and Development Program of China

National Natural Science Foundation of China

Natural Science Foundation of Hebei Province

Publisher

Wiley

Subject

General Chemical Engineering,General Chemistry,Human Factors and Ergonomics

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/col.22491

Reference48 articles.

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2. LinP LinB. Fuzzy automatic contrast enhancement based on fuzzy C‐means clustering in CIELAB color space. Paper presented at: 12th IEEE/ASME International Conference on Mechatronic and Embedded Systems and Applications (MESA); August 29‐31 2016 Auckland New Zealand.

3. A color clustering technique for image segmentation

4. Color Clustering and Learning for Image Segmentation Based on Neural Networks

5. ChenT ChenY ChenS. Fast image segmentation based on K‐means clustering with histograms in HSV color space. Paper presented at: IEEE 10th Workshop on Multimedia Signal Processing; October 8‐10 2008 Queensland Australia.

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