Effective Segmentation Approach for Solar Photovoltaic Panels in Uneven Illuminated Color Infrared Images

Nan Wang, Zhan Li Sun, Zhigang Zeng, Kin Man Lam

Research output: Journal article publicationJournal articleAcademic researchpeer-review

Abstract

How to accurately segment a solar photovoltaic panel in an infrared image is an intractable problem due to some unfavorable factors. In this article, an effective approach is proposed for solar photovoltaic panel segmentation from infrared images. In order to alleviate the effect of uneven color distribution, a guided filter-based image-enhancement method is first devised to strengthen the edges of solar photovoltaic panels. Moreover, a two-stage method is proposed to detect the contour lines of solar photovoltaic panels. In our algorithm, first, after a thresholding operation, contours in the images are detected by means of a line-segment detector. Then, a method based on k-means clustering is employed to eliminate lines caused by noise or irrelevant background areas. In addition, a background-subtraction strategy is designed to achieve a more accurate segmentation result by removing the remaining background regions. Experimental results demonstrate the effectiveness and efficiency of the proposed method for the segmentation of solar photovoltaic panels.

Original languageEnglish
Article number9292949
Pages (from-to)478-484
Number of pages7
JournalIEEE Journal of Photovoltaics
Volume11
Issue number2
DOIs
Publication statusPublished - Mar 2021

Keywords

  • Image enhancement
  • image segmentation
  • k-means clustering
  • solar photovoltaic panel
  • straight line detection

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Electrical and Electronic Engineering

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