Journal of Central South University

, Volume 25, Issue 6, pp 1501–1512 | Cite as

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

  • Zu-guo Chen (陈祖国)
  • Yong-gang Li (李勇刚)Email author
  • Xiao-fang Chen (陈晓方)
  • Chun-hua Yang (阳春华)
  • Wei-hua Gui (桂卫华)


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.

Key words

edge and texture detection GEAF-CCI algorithm DTMLGE algorithm metal image 



锌锭铸造是一个高温、高粉尘和动态凝固的复杂过程。为了准确地检测该条件下金属图像的边 缘和纹理特征,提出了一种基于梯度熵和自适应四阶立方卷积插值的亚像素检测算法(GEAF-CCI)。该 方法主要包含3 个过程:首先,采用梯度算子从灰度图像中生成梯度图像;然后,采用基于最大局部 梯度熵的动态阈值(DTMLGE)算法去区分梯度图像中的边缘和纹理的像素;最后,使用AF-CCI 算 法根据目标边缘和纹理在不同方向的变化差异对其进行插值计算。实验结果表明,该算法可以减少细 节模糊和边缘锯齿现象的产生,提高边缘的定位精度和降低误检率和失检率。


边缘与纹理检测 GEAF-CCI 算法 DTMLGE 算法 金属图像 


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Copyright information

© Central South University Press and Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.School of Information Science and EngineeringCentral South UniversityChangshaChina

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