Region-based Image Segmentation by Watershed Partition and DCT Energy Compaction

DOI

10.1080/18756891.2012.670521How to use a DOI?

Keywords

image segmentation, energy compaction, cosine transform, watershed

Abstract

An image segmentation approach by improved watershed partition and DCT energy compaction has been proposed in this paper. The proposed energy compaction, which expresses the local texture of an image area, is derived by exploiting the discrete cosine transform. The algorithm is a hybrid segmentation technique which is composed of three stages. First, the watershed transform is utilized by preprocessing techniques: edge detection and marker in order to partition the image in to several small disjoint patches, while the region size, mean and variance features are used to calculate region cost for combination. Then in the second merging stage the DCT transform is used for energy compaction which is a criterion for texture comparison and region merging. Finally the image can be segmented into several partitions. The experimental results show that the proposed approach achieved very good segmentation robustness and efficiency, when compared to other state of the art image segmentation algorithms and human segmentation results.

Copyright

© 2017, 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  - JOUR
AU  - Chi-Man Pun
AU  - Ning-Yu An
AU  - C.L. Philip Chen
PY  - 2012
DA  - 2012/02/01
TI  - Region-based Image Segmentation by Watershed Partition and DCT Energy Compaction
JO  - International Journal of Computational Intelligence Systems
SP  - 53
EP  - 64
VL  - 5
IS  - 1
SN  - 1875-6883
UR  - https://doi.org/10.1080/18756891.2012.670521
DO  - 10.1080/18756891.2012.670521
ID  - Pun2012
ER  -