• Priyanka Rani
• Vikas Kumar

Local anomalies in a single panel such as hotspots and cracks will be immediately detected and labeled as soon as the panel is recognized in the field of view. In our research, we propose a solar panel defect detection system, which give a novel method for solar image defect detect makes use of Discrete Wavelet transform based principal Component Analysis (DWTPCA) for feature extraction from the non-overlapping sub-windows of texture images and classifies a sub-window as defective or non-defective according to Euclidean distance between the feature obtained from average value of the features of a defect free sample and the feature obtained from one sub-window of a test image.

solar cell imagining, Cascade vision, optical flow, PCA (principle components analysis) , Independent component analysis, DWT, etc

"Implementation Of Pca And Dwtpca On Solar Cells For Detection Of Defects", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 3, page no.83-88, March-2019, Available :http://www.jetir.org/papers/JETIR1903912.pdf

"Implementation Of Pca And Dwtpca On Solar Cells For Detection Of Defects", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 3, page no. pp83-88, March-2019, Available at : http://www.jetir.org/papers/JETIR1903912.pdf