Remote Solar Panels Identification Based on Patterns Localization

Solar panels inspection is an essential task that must be routinely performed by solar plant supervisors in the purpose of maintaining an acceptable energy production. Such task requires a regular assessment of all the solar panels installed in the solar farm. This constraint requires assigning an important financial budget as well as a qualified technical staff. However, integrating an automatic assessment system seems more financially beneficial, especially in terms of mitigating the need for manual panels inspection. The proposed inspection system comprises a Unmanned Aerial Vehicle (UAV) provided with a processing unit (based on embedded system architecture) and HD camera. Actually, before skipping to solar panels state evaluation, each panel must be beforehand localized and extracted from the captured video frames (images). In this paper, we propose a standalone system which allows to localize and crop separately solar panels from video frames. Each panel localization is ensured through a well-defined 4 localization patterns, put on the 4 panel corners. These patterns are then localized by means of a specific scanning process which browses the captured image into two directions (horizontal and vertical) and retains all segments whose the structure is characterized by the ration 1:1:1:1:3:1:1:1:1 (describing pattern structure). Basing on the carried out experiments, our conceived approach turned out less computationally expensive compared to the approaches which are based on edge detectors (e.g. Hough transform), linear regression or infrared imagery.