- Author
- Gang WANG and Bernard De Baets (UGent)
- Organization
- Abstract
- Superpixel segmentation can benefit from the use of an appropriate method to measure edge strength. In this paper, we present such a method based on the first derivative of anisotropic Gaussian kernels. The kernels can capture the position, direction, prominence, and scale of the edge to be detected. We incorporate the anisotropic edge strength into the distance measure between neighboring superpixels, thereby improving the performance of an existing graph-based superpixel segmentation method. Experimental results validate the superiority of our method in generating superpixels over the competing methods. It is also illustrated that the proposed superpixel segmentation method can facilitate subsequent saliency detection.
- Keywords
- edge strength, first derivative of anisotropic Gaussian kernel, superpixel segmentation, distance measure, graph-based method, CONTOUR-DETECTION, NOISE
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Citation
Please use this url to cite or link to this publication: http://hdl.handle.net/1854/LU-8626844
- MLA
- WANG, Gang, and Bernard De Baets. “Superpixel Segmentation Based on Anisotropic Edge Strength.” JOURNAL OF IMAGING, vol. 5, no. 6, 2019, doi:10.3390/jimaging5060057.
- APA
- WANG, G., & De Baets, B. (2019). Superpixel segmentation based on anisotropic edge strength. JOURNAL OF IMAGING, 5(6). https://doi.org/10.3390/jimaging5060057
- Chicago author-date
- WANG, Gang, and Bernard De Baets. 2019. “Superpixel Segmentation Based on Anisotropic Edge Strength.” JOURNAL OF IMAGING 5 (6). https://doi.org/10.3390/jimaging5060057.
- Chicago author-date (all authors)
- WANG, Gang, and Bernard De Baets. 2019. “Superpixel Segmentation Based on Anisotropic Edge Strength.” JOURNAL OF IMAGING 5 (6). doi:10.3390/jimaging5060057.
- Vancouver
- 1.WANG G, De Baets B. Superpixel segmentation based on anisotropic edge strength. JOURNAL OF IMAGING. 2019;5(6).
- IEEE
- [1]G. WANG and B. De Baets, “Superpixel segmentation based on anisotropic edge strength,” JOURNAL OF IMAGING, vol. 5, no. 6, 2019.
@article{8626844, abstract = {{Superpixel segmentation can benefit from the use of an appropriate method to measure edge strength. In this paper, we present such a method based on the first derivative of anisotropic Gaussian kernels. The kernels can capture the position, direction, prominence, and scale of the edge to be detected. We incorporate the anisotropic edge strength into the distance measure between neighboring superpixels, thereby improving the performance of an existing graph-based superpixel segmentation method. Experimental results validate the superiority of our method in generating superpixels over the competing methods. It is also illustrated that the proposed superpixel segmentation method can facilitate subsequent saliency detection.}}, articleno = {{57}}, author = {{WANG, Gang and De Baets, Bernard}}, issn = {{2313-433X}}, journal = {{JOURNAL OF IMAGING}}, keywords = {{edge strength,first derivative of anisotropic Gaussian kernel,superpixel segmentation,distance measure,graph-based method,CONTOUR-DETECTION,NOISE}}, language = {{eng}}, number = {{6}}, pages = {{24}}, title = {{Superpixel segmentation based on anisotropic edge strength}}, url = {{http://doi.org/10.3390/jimaging5060057}}, volume = {{5}}, year = {{2019}}, }
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