| 한글제목(Korean Title) |
A New Connected Coherence Tree Algorithm For Image Segmentation |
| 영문제목(English Title) |
A New Connected Coherence Tree Algorithm For Image Segmentation |
| 저자(Author) |
Jingbo Zhou
Shangbing Gao
Zhong Jin
|
| 원문수록처(Citation) |
VOL 06 NO. 04 PP. 1188 ~ 1202 (2012. 04) |
한글내용
(Korean Abstract) |
|
영문내용
(English Abstract) |
In this paper, we propose a new multi-scale connected coherence tree algorithm (MCCTA) by improving the connected coherence tree algorithm (CCTA). In contrast to many multi-scale image processing algorithms, MCCTA works on multiple scales space of an image and can adaptively change the parameters to capture the coarse and fine level details. Furthermore, we design a Multi-scale Connected Coherence Tree algorithm plus Spectral graph partitioning (MCCTSGP) by combining MCCTA and Spectral graph partitioning in to a new framework. Specifically, the graph nodes are the regions produced by CCTA and the image pixels, and the weights are the affinities between nodes. Then we run a spectral graph partitioning algorithm to partition on the graph which can consider the information both from pixels and regions to improve the quality of segments for providing image segmentation. The experimental results on Berkeley image database demonstrate the accuracy of our algorithm as compared to existing popular methods. |
| 키워드(Keyword) |
CCTA
graph-based
image segmentation
multi-scale
spectral graph partitioning
|
| 파일첨부 |
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