Image De-Noising and Micro Crack Detection of Solar Cells

Solar cell is known as a sustainable and environment friendly source of energy in nature. It converts sunlight directly into electricity with zero emission and also without side-effects on the environment. But, solar cells have optical and mechanical defects which include the type of micro crack, the size of crack, and the noise from electrical or electromechanical interference during the image acquisition. This paper through image processing techniques presents several groups of methods to compare between two types of solar cell images, which are from solar cells with crack and without crack. In the first step, there are some methods such as Gaussian filter, Diffusion filter, Wavelet filter; Fast Fourier Transform and notch filter to de-noise images. In the next level, the study presents Gray Level Co-occurrence Matrix (GLCM) method to feature extraction of images and also the Hough transform to perform crack detection and analysis. Finally, the results confirm that the image from the solar cell with crack has the highest “S” measure compared to good images which have lower “S” measure levels.