Research and Application on Tangka Image Segmentation Algorithm

DOI

10.2991/icmmita-15.2015.17How to use a DOI?

Keywords

Tangka image; segmentation algorithm; image segmentation; clustering analysis; multi-feature combination.

Abstract

This paper studies the key problems of many Tangka image segmentation algorithms and computational complexity and hard to applies to large scale images segmentation. As a exploratory research of Tangka image, the paper fully took the comprehensive and robustness of algorithm into account. The image segmentation based on saliency area detection had nice translational, multi feature combination and rotational invariance, so we focus on image segmentation. First, design the algorithm based on clustering analysis theory and segments the fuzzy image, especially the fuzzy edge. Then we improve the Tangka segmentation algorithm in order to meet high precision of the application. Meanwhile, Tangka image segmentation offer convenience for research in future, and the final recognition result was satisfy us according to the experiment.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Yan Xu
AU  - WeiLan Wang
PY  - 2015/11
DA  - 2015/11
TI  - Research and Application on Tangka Image Segmentation Algorithm
BT  - Proceedings of the 2015 3rd International Conference on Machinery, Materials and Information Technology Applications
PB  - Atlantis Press
SP  - 74
EP  - 77
SN  - 2352-538X
UR  - https://doi.org/10.2991/icmmita-15.2015.17
DO  - 10.2991/icmmita-15.2015.17
ID  - Xu2015/11
ER  -