In my major project, image preprocessing played a pivotal role in enhancing data quality. I employed a multi-step approach that included resizing images for uniformity, applying normalization to standardize pixel values, and implementing histogram equalization to improve contrast. Additionally, noise reduction techniques, such as Gaussian blurring, were applied to ensure cleaner data. This comprehensive preprocessing pipeline aimed at optimizing image inputs for subsequent machine learning algorithms, ultimately improving model performance.