Edge and texture detection of metal image under high temperature and dynamic solidification condition View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2018-06

AUTHORS

Zu-guo Chen, Yong-gang Li, Xiao-fang Chen, Chun-hua Yang, Wei-hua Gui

ABSTRACT

The zinc casting is a complicated process with high temperature, high dust content and dynamic solidification. To accurately detect the edge and texture of metal image under this condition, a sub-pixel detection based on gradient entropy and adaptive four-order cubic convolution interpolation (GEAF-CCI) algorithm is proposed. This method mainly involves three procedures. Firstly, the gradient image is generated from the grey images by using gradient operator. Then, a dynamic threshold based on the maximum local gradient entropy (DTMLGE) algorithm is applied to distinguishing the edge and texture pixels from gradient images. Finally, the adaptive four-order cubic convolution interpolation (AF-CCI) algorithm is proposed for interpolating calculation of the target edges and textures according to their variation differences in different directions. The experimental result shows that the proposed algorithm can remove the jag and blur of the edges and textures, improve the edge positioning precision and reduce the false or missing detection rate. More... »

PAGES

1501-1512

References to SciGraph publications

  • 2005-05. Zinc Casting and Recycling (8 pp) in THE INTERNATIONAL JOURNAL OF LIFE CYCLE ASSESSMENT
  • 2011-12. Modeling and control of copper loss in smelting slag in JOM
  • 2016-02. An improved sobel edge detection method based on generalized type-2 fuzzy logic in SOFT COMPUTING
  • 2015-06. Edge Detection Using Topological Gradients: A Scale-Space Approach in JOURNAL OF MATHEMATICAL IMAGING AND VISION
  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1007/s11771-018-3843-3

    DOI

    http://dx.doi.org/10.1007/s11771-018-3843-3

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