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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Donoser, M. Bischof, H. |
| Copyright Year | 2007 |
| Description | Author affiliation: Graz Univ. of Technol., Styria (Donoser, M.; Bischof, H.) |
| Abstract | This paper presents a novel unsupervised color segmentation scheme named ROI-SEG, which is based on the main idea of combining a set of different sub-segmentation results. We propose an efficient algorithm to compute sub-segmentations by an integral image approach for calculating Bhattacharyya distances and a modified version of the maximally stable extremal region (MSER) detector. The sub-segmentation algorithm gets a region-of-interest (ROI) as input and detects connected regions having similar color appearance as the ROI. We further introduce a method to identify ROIs representing the predominant color and texture regions of an image. Passing each of the identified ROIs to the sub-segmentation algorithm provides a set of different segmentations, which are then combined by analyzing a local quality criterion. The entire approach is fully unsupervised and does not need a priori information about the image scene. The method is compared to state-of-the-art algorithms on the Berkeley image database, where it shows competitive results at reduced computational costs. |
| Starting Page | 1 |
| Ending Page | 8 |
| File Size | 3565592 |
| Page Count | 8 |
| File Format | |
| ISBN | 1424411793 |
| ISSN | 10636919 |
| DOI | 10.1109/CVPR.2007.383231 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2007-06-17 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Image segmentation Color Detectors Partitioning algorithms Focusing Algorithm design and analysis Layout Image databases Computer graphics Computational efficiency |
| Content Type | Text |
| Resource Type | Article |
| Subject | Computer Vision and Pattern Recognition Software |
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