计算机与现代化 ›› 2020, Vol. 0 ›› Issue (08): 26-30.doi: 10.3969/j.issn.1006-2475.2020.08.005

• 图像处理 • 上一篇    下一篇

基于红外可见光图像配准的电力设备分割算法

  

  1. (1.国网江苏省电力有限公司常州供电分公司运维检修部,江苏常州213000;2.河海大学物联网工程学院,江苏常州213022;
    3.江苏亚威变压器有限公司,江苏南通226600)
  • 收稿日期:2019-12-05 出版日期:2020-08-17 发布日期:2020-08-17
  • 作者简介:刘晓康(1986-),男,江苏武进人,工程师,硕士,研究方向:电气工程,E-mail: 70551313@qq.com; 万曦(1989-),男,工程师,硕士,研究方向:绝缘介质的性能与放电现象,人工神经网络,E-mail: 623629713@qq.com; 涂文超(1994-),男,助理工程师,硕士,研究方向:继电保护,E-mail: 863528129@qq.com。
  • 基金资助:
    江苏省重点研发计划项目(产业前瞻与共性关键技术——竞争项目)(BE2018092)

Power Equipment Segmentation Algorithm Based on Infrared and Visible Images Registration

  1. (1. Operation and Maintenance Department of Changzhou Power Supply Branch of State Grid Jiangsu Electric Power Co. Ltd.
    Changzhou 213000, China;2. IoT Engineering College of Hohai University, Changzhou 213022, China;
    3. Jiangsu Yawei Transformer Co. Ltd.〖KG-*3〗, Nantong 226600, China)
  • Received:2019-12-05 Online:2020-08-17 Published:2020-08-17

摘要: 电力设备故障会导致变电站大范围停电,造成巨大损失。根据电力设备运行时会发热的特点,提出一种基于红外可见光图像配准的电力设备分割方法,便于进行故障检测。该方法首先利用结构化随机森林对电力设备的红外和可见光图像进行边缘检测,构建可见光边缘图像的多尺度高斯金字塔,然后结合归一化互信息对红外和可见光图像进行配准,对红外图像进行Otsu阈值分割,结合配准结果分割出可见光图像中的电力设备。实验结果表明,该算法能精确地实现配准及分割,具有一定实用性。

关键词: 图像分割, 电力设备, 图像配准, 归一化互信息, 边缘, 结构化随机森林, 高斯金字塔

Abstract: The fault of power equipment may cause large-scale power outages in substations, bringing out huge losses. According to the characteristics of heat generation during operation of power equipment, a power equipment segmentation method based on infrared and visible images registration is proposed to facilitate fault detection. Firstly, the structured random forest is used to detect the edge of infrared and visible images of the power equipment, and a multi-scale Gaussian pyramid of the visible edge image is constructed. Then the infrared and visible images are registered with the normalized mutual information. Finally, the Otsu threshold segmentation result of the infrared image is combined with the registration result to segment the power equipment in the visible image. The experimental results show that the proposed algorithm can register and segment accurately, and it has certain practicability.

Key words: image segmentation, power equipment, image registration, normalized mutual information, edge, structured random forest, Gaussian pyramid

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