The demand for sustainable energy solutions has spurred advancements in solar technologies, where optimal alignment of solar panels is crucial for maximizing efficiency. This study introduces a MATLAB-based image processing approach for automatic sun position tracking to enhance solar panel performance. Utilizing a digital camera, real-time sky images are captured and processed to detect the sun’s position through image filtering, edge detection, and centroid calculation. Advanced algorithms distinguish the sun from other bright objects and noise, allowing dynamic adjustment of panel angles via a motorized mechanism to maintain optimal alignment. Simulations and experiments demonstrate significant energy capture improvements, with efficiency gains up to 30%. The system’s adaptability to varying weather conditions underscores its potential for widespread application. This research highlights the feasibility of combining image processing with renewable energy systems and suggests future work in algorithm refinement and machine learning integration to further optimize solar tracking and energy yield.