Combining external prior and internal features: toward a robust foreground seed selection method
| Autor: | Xiong Yunbo, Huibin Wang, Chao Zhu, Lizhong Xu, Zhen Zhang |
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| Rok vydání: | 2019 |
| Předmět: |
Correctness
Computer science business.industry Feature extraction Boundary (topology) Pattern recognition Image processing 02 engineering and technology Image segmentation Atomic and Molecular Physics and Optics Computer Science Applications Image (mathematics) 0202 electrical engineering electronic engineering information engineering Graph (abstract data type) 020201 artificial intelligence & image processing Artificial intelligence Electrical and Electronic Engineering business Selection (genetic algorithm) |
| Zdroj: | Journal of Electronic Imaging. 28:1 |
| ISSN: | 1017-9909 |
| Popis: | Graph-based salient object detection has been widely applied in many applications, because of its excellent performance and strong theoretical basis. Basically, the performance of this type of methods depends on the correctness in foreground seed selection. In research aiming to exactly identify the seeds on foreground objects, an external prior has been defined in recent work as having an image boundary that is mostly background (called boundary prior), so the foreground seeds must locate around the image center. However, this is not the case when salient objects are spatially close to the image boundary. This problem will cause a severe error in salient object detection, because background noises are likely mixed in foreground seeds. To solve this problem, we propose a robust foreground seed selection method for salient object detection. In our method, the external prior and multiple internal image features are combined for foreground seed selection. Our method can relax the limitation of the external prior and make the foreground seed selection more adaptive and robust to diverse samples. As a result, the proposed method can generate satisfying results, no matter where the salient object is located. This advantage is demonstrated by experimental comparisons with several state-of-art methods. |
| Databáze: | OpenAIRE |
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