TY - JOUR
T1 - Effective Segmentation Approach for Solar Photovoltaic Panels in Uneven Illuminated Color Infrared Images
AU - Wang, Nan
AU - Sun, Zhan Li
AU - Zeng, Zhigang
AU - Lam, Kin Man
N1 - Funding Information:
Manuscript received September 3, 2020; revised November 4, 2020; accepted November 17, 2020. Date of publication December 14, 2020; date of current version February 19, 2021. The work was supported by the National Natural Science Foundation of China under Grant 61972002. (Corresponding author: Zhan-Li Sun.) Nan Wang is with the Key Laboratory of Intelligent Computing and Signal Processing, Ministry of Education, School of Electrical Engineering and Automation, Anhui University, Hefei 230039, China, and also with the Hefei Sunwin Intelligence Company Ltd., Hefei 230022, China (e-mail: [email protected]).
Publisher Copyright:
© 2011-2012 IEEE.
PY - 2021/3
Y1 - 2021/3
N2 - 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.
AB - 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.
KW - Image enhancement
KW - image segmentation
KW - k-means clustering
KW - solar photovoltaic panel
KW - straight line detection
UR - http://www.scopus.com/inward/record.url?scp=85098767043&partnerID=8YFLogxK
U2 - 10.1109/JPHOTOV.2020.3041189
DO - 10.1109/JPHOTOV.2020.3041189
M3 - Journal article
AN - SCOPUS:85098767043
SN - 2156-3381
VL - 11
SP - 478
EP - 484
JO - IEEE Journal of Photovoltaics
JF - IEEE Journal of Photovoltaics
IS - 2
M1 - 9292949
ER -
