计算机与现代化

• 图像处理 • 上一篇    下一篇

一种改进的基于上下文的破损显著性检测

  

  1. 东华大学信息科学与技术学院,上海201620
  • 收稿日期:2015-04-27 出版日期:2015-09-21 发布日期:2015-09-24
  • 作者简介:丁曹凯(1990-),女,江苏泰州人,东华大学信息科学与技术学院硕士研究生,研究方向:图像处理; 通讯作者:周武能(1959-),男,教授,博士生导师,博士,研究方向:神经网络,图像处理, 控制理论。
  • 基金资助:
     上海市自然科学基金资助项目(15ZR1401800)

 A Breakage Detection Based on Context-aware Saliency Detection

  1. College of Information Science and Technology, Donghua University, Shanghai 201620, China
  • Received:2015-04-27 Online:2015-09-21 Published:2015-09-24

摘要:

采用简单的图像分割和边缘提取对工业透明塑料薄膜的破损情况进行检测时,效果不太理想。针对这种情况,本文提出一种改进的基于上下文的工业透明薄膜包装破损显著性检测。首先对
拍摄的图像进行点Hough变换(PHT),然后将PHT变换的图像进行Graph-based超像素分割,最后对超像素分割后的图像进行基于上下文的显著性检测。实验结果表明,本方法准确性高、运行时间短,在工
业上的应用具有可行性。

关键词:  , 点霍夫变换, 图论, 超像素, 改进的显著性检测

Abstract:

It is not the best idea of using a simple way of image segmentation and edge detection in detecting the breakage of transparent plastics in industrial area. For
this, a breakage detection based on context-aware saliency detection which is employed in the transparent plastics in industrial area is proposed. First, we carry out the point
Hough transform (PHT) on the original image. Then the graph-based superpixel segmentation is used to segment the image after the PHT. Finally, context-aware saliency detection
is used to detect the salient area of the image. The experiments show that the method is of high accuracy and short run time.

Key words:  point Hough transform (PHT), graph-based, superpixel, improved saliency detection