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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Jungmann, Alexander Jatzkowski, Jan Kleinjohann, Bernd |
| Copyright Year | 2014 |
| Description | Author affiliation: Cooperative Computing & Communication Laboratory, University of Paderborn, Fuerstenallee 11, Germany (Jungmann, Alexander; Jatzkowski, Jan; Kleinjohann, Bernd) |
| Abstract | In this paper, we evaluate the robustness of our color-based segmentation approach in combination with different color spaces, namely RGB, L*a*b*, HSV, and log-chromaticity (LCCS). For this purpose, we describe our deterministic segmentation algorithm including its gradually transformation of pixel-precise image data into a less error-prone and therefore more robust statistical representation in terms of moments. To investigate the robustness of a specific segmentation setting, we introduce our evaluation framework that directly works on the statistical representation. It is based on two different types of robustness measures, namely relative and absolute robustness. While relative robustness measures stability of segmentation results over time, absolute robustness measures stability regarding varying illumination by comparing results with ground truth data. The significance of these robustness measures is shown by evaluating our segmentation approach with different color spaces. For the evaluation process, an artificial scene was chosen as representative for application scenarios based on artificial landmarks. |
| Starting Page | 648 |
| Ending Page | 655 |
| File Size | 1658577 |
| Page Count | 8 |
| File Format | |
| ISBN | 9789897581335 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2014-01-05 |
| Publisher Place | Portugal |
| Access Restriction | Subscribed |
| Rights Holder | SCITEPRESS |
| Subject Keyword | Image segmentation Evaluation of Segmentation Results Image Processing Color-based Segmentation Color Spaces |
| Content Type | Text |
| Resource Type | Article |
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