Abstract
This paper adopts SLIC-based superpixel segmentation method in the granular image detection. SLIC method segments the granular image into superpixel block which will reduce the complexity of the subsequent image processing. As SLIC superpixel segmentation method doesn’t use the texture feature in the distance calculation, the detail of the outline for the granular object is lost. This paper adopts the CRLBP local texture operator as the texture feature to improve the SLIC segmentation’s distance calculation and searches the similar pixel in circle neighborhood pixels to guarantee the processing speed. The test on cotton seed image shows that the improved SLIC superpixel segmentation method is more efficient than watershed and original SLIC method.
Publication Date
12-28-2016
First Page
31
Last Page
34,39
DOI
10.13652/j.issn.1003-5788.2016.12.007
Recommended Citation
Xiaoyu, LI and Qiuju, ZHANG
(2016)
"A SLIC-basedsuperpixel segmentation method by using local texture features for granular image,"
Food and Machinery: Vol. 32:
Iss.
12, Article 7.
DOI: 10.13652/j.issn.1003-5788.2016.12.007
Available at:
https://www.ifoodmm.cn/journal/vol32/iss12/7
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