An Improved Remote Sensing Image Classification Based on K-Means Using HSV Color Feature

An improved classification method based on KMeans using HSV color feature is introduced in this paper. It is implemented by extracting three color features (hue, saturation, value) for K-Means clustering. Compared with the traditional K-Means clustering, the experimental results turn out that our pr...

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Bibliographic Details
Published in2014 Tenth International Conference on Computational Intelligence and Security pp. 201 - 204
Main Authors Wu, Shulei, Chen, Huandong, Zhao, Zhizhong, Long, Haixia, Song, Chunhui
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.11.2014
Subjects
Accuracy
Classification algorithms
Color Feature
Educational institutions
Feature extraction
HSV
Image classification
Image color analysis
Remote sensing
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DOI10.1109/CIS.2014.90

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Summary:An improved classification method based on KMeans using HSV color feature is introduced in this paper. It is implemented by extracting three color features (hue, saturation, value) for K-Means clustering. Compared with the traditional K-Means clustering, the experimental results turn out that our proposed method is better than K-Means in classification accuracy and performance.
DOI:10.1109/CIS.2014.90