Systematic Benchmarking of Aerial Image Segmentation
| Autor: | Anil Cheriyadat, Jiangye Yuan, Shaun S. Gleason |
|---|---|
| Rok vydání: | 2013 |
| Předmět: |
Ground truth
Segmentation-based object categorization business.industry Computer science ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Scale-space segmentation Image segmentation Geotechnical Engineering and Engineering Geology Automatic image annotation Minimum spanning tree-based segmentation Image texture Region growing Computer vision Segmentation Artificial intelligence Electrical and Electronic Engineering business Aerial image Feature detection (computer vision) |
| Zdroj: | IEEE Geoscience and Remote Sensing Letters. 10:1527-1531 |
| ISSN: | 1558-0571 1545-598X |
| DOI: | 10.1109/lgrs.2013.2261453 |
| Popis: | This letter presents a benchmarking study for aerial image segmentation. We construct an image data set consisting of various aerial scenes. Segmentations generated by different human subjects are used as ground truth. We analyze the consistency between segmentations from different subjects. We select six leading segmentation algorithms, which include not only the algorithms specifically designed for aerial images but also more generally applicable algorithms. We also select a recently proposed algorithm due to its promising performance in handling texture regions. We apply these algorithms to the aerial image data set and quantitatively evaluate their performance. We interpret the evaluation results based on the characteristics of algorithms, which provide general guidance for selecting proper algorithms in specific applications. |
| Databáze: | OpenAIRE |
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