Recent Facial Image Preprocessing Techniques: A Review - Rendra Soekarta; Ku Ruhana Ku-Mahamud (Engineering Proceedings, 2025)
This review analyzes recent advancements in facial recognition and classification algorithms, emphasizing the critical role of preprocessing techniques in enhancing the algorithms’ accuracy, reliability, and efficiency. Facial image preprocessing is a critical step in various applications, including facial recognition, emotion detection, and biometric authentication. Preprocessing methods including normalization, noise reduction, illumination correction, alignment, resolution enhancement, data augmentation, and edge detection are essential for improving image quality and standardizing facial features in improving facial image quality. The review explores the strengths and weaknesses of these techniques across different facial datasets. The ongoing refinement of preprocessing techniques will be pivotal in advancing facial recognition, classification, and other image-based tasks. Finally, this paper provides insights into the future directions of research. As the demand for more robust, fair, and efficient systems grows, developing domain-specific preprocessing methods and adopting cutting-edge artificial intelligence technologies will be vital to meet the challenges of increasingly complex applications.