The integration of deep learning with digital image processing has revolutionized the field of feature extraction, leading to significant advancements in various image analysis applications. This research paper explores the synergistic combination of deep learning techniques, particularly convolutional neural networks (CNNs), with traditional digital image processing methods to enhance feature extraction from complex image datasets. By leveraging the hierarchical feature learning capabilities of deep learning, combined with the precision and efficiency of classical image processing algorithms, our approach aims to achieve superior accuracy and robustness in feature extraction tasks.