@inproceedings{912ffca5e3d44abf8b720bb52612f82c,
title = "Towards a Hybrid Approach of K-Means and Density-Based Spatial Clustering of Applications with Noise for Image Segmentation",
abstract = "Image segmentation is the process to divide a digital image into a number of regions for further analysis in the area of computer vision. Color images can be segmented by applying various clustering algorithms such as DBSCAN, which can identify the arbitrary shaped clusters. The drawback of DBSCAN is the high computational complexity whilst the sizes of image datasets are normally very large. This paper proposes a hybrid method of K-means and DBSCAN (Kmeans-DBSCAN) for image segmentation. K-means is the common partition-based clustering approach to reduce the size of image dataset. Four benchmarking image segmentation cases are used for evaluating the usability of proposed Kmeans-DBSCAN method.",
keywords = "Clustering Analysis, Computer Vision, DBSCAN, Image Segmentation, K-means",
author = "Chun Guan and Yuen, {Kevin Kam Fung} and Qi Chen",
note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; Joint 10th IEEE International Conference on Internet of Things, iThings 2017, 13th IEEE International Conference on Green Computing and Communications, GreenCom 2017, 10th IEEE International Conference on Cyber, Physical and Social Computing, CPSCom 2017 and the 3rd IEEE International Conference on Smart Data, Smart Data 2017 ; Conference date: 21-06-2017 Through 23-06-2017",
year = "2017",
month = jul,
day = "2",
doi = "10.1109/iThings-GreenCom-CPSCom-SmartData.2017.65",
language = "English",
series = "Proceedings - 2017 IEEE International Conference on Internet of Things, IEEE Green Computing and Communications, IEEE Cyber, Physical and Social Computing, IEEE Smart Data, iThings-GreenCom-CPSCom-SmartData 2017",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "396--399",
editor = "Yulei Wu and Geyong Min and Nektarios Georgalas and Ahmed Al-Dubi and Xiaolong Jin and Yang, {Laurence T.}",
booktitle = "Proceedings - 2017 IEEE International Conference on Internet of Things, IEEE Green Computing and Communications, IEEE Cyber, Physical and Social Computing, IEEE Smart Data, iThings-GreenCom-CPSCom-SmartData 2017",
}
