Image Co-Segmentation via Examples Guidance
| Autor: | Imane Daoudi, Rachida Es-salhi, Hamid El Ouardi |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
General Computer Science
business.industry Computer science ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION 020207 software engineering Pattern recognition 02 engineering and technology Image segmentation Robustness (computer science) 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Segmentation Artificial intelligence business |
| Zdroj: | International Journal of Advanced Computer Science and Applications. 10 |
| ISSN: | 2156-5570 2158-107X |
| DOI: | 10.14569/ijacsa.2019.0100165 |
| Popis: | Given a collection of images which contains objects from the same category, the co-segmentation methods aim at simultaneously segmenting such common objects in each image. Most of existing co-segmentation approaches rely on comput-ing similarities inter-regions representing foregrounds in these images. However, region similarity measurement is challenging due to the large appearance variations among objects in the same category. In addition, for real-world images which have cluttered backgrounds, the existing co-segmentation approaches miss sufficient robustness to extract the common object from the background. In this paper, we propose a new co-segmentation method which takes advantage of the reliable segmentation of few selected images, in order to guide the segmentation of the remaining images in the collection. A random sample of images is first selected from the image collection. Then, the selected images are segmented using an interactive segmentation method. These segmentation results are used to construct positive/negative samples of the targeted common object and background regions respectively. Finally, these samples are propagated to the remain-ing images in the collection through computing both local and global consistency. The experiments on the iCoseg and MSRC datasets demonstrate the performance and robustness of the proposed method. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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