Grain Segmentation of Solar Cell Wafers Using Region Growing

In the era of rapid high-technology growth, the energy allocation problem influences not only in economic development, but also seriously affects the environment and ecology. Recently, solar power becomes an attractive alternative source of energy. The multi-crystalline solar cell has been widely accepted in the market due to its significantly reduced manufacturing cost. Multi-crystalline solar wafers own larger average grain size surfaces and less grain boundaries that bring about higher quality and conversion efficiency. In this article, we propose a new image processing method to segment solar wafers for grain analysis. The pre-processing step via a median filter is applied first for the image contrast enhancement. Then, an adaptive segmentation algorithm based on region growing is developed, with an attempt to retain the fast algorithmic convergence and appropriate regional growth. The separate closed regions, called grain, are culled from the wafer by using the proposed region growing algorithm, and then the average grain size and number on a single wafer surface can be evaluated to dictate the quality of solar wafers in conversion efficiency.