An Overview of Contour Detection Approaches
| Autor: | Xinyi Gong, Hua-Bin Yang, Fei Shen, De Xu, Zhengtao Zhang, Hu Su |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
Active contour model
Contextual image classification business.industry Computer science Applied Mathematics ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Object contour Pattern recognition 02 engineering and technology Convolutional neural network Computer Science Applications 03 medical and health sciences 0302 clinical medicine Control and Systems Engineering Modeling and Simulation 0202 electrical engineering electronic engineering information engineering Gestalt psychology 020201 artificial intelligence & image processing Segmentation Artificial intelligence business 030217 neurology & neurosurgery ComputingMethodologies_COMPUTERGRAPHICS |
| Zdroj: | International Journal of Automation and Computing. 15:656-672 |
| ISSN: | 1751-8520 1476-8186 |
| Popis: | Object contour plays an important role in fields such as semantic segmentation and image classification. However, the extraction of contour is a difficult task, especially when the contour is incomplete or unclosed. In this paper, the existing contour detection approaches are reviewed and roughly divided into three categories: pixel-based, edge-based, and region-based. In addition, since the traditional contour detection approaches have achieved a high degree of sophistication, the deep convolutional neural networks (DCNNs) have good performance in image recognition, therefore, the DCNNs based contour detection approaches are also covered in this paper. Moreover, the future development of contour detection is analyzed and predicted. |
| Databáze: | OpenAIRE |
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