This study illustrates that image preprocessing substantially influences the precision of wrinkle identification in human skin utilizing Convolutional Neural Networks. The CLAHE methodology is the most efficacious standalone preprocessing strategy for enhancing model performance. The integration of CLAHE with sharpening achieves the highest accuracy while maintaining an optimal balance between precision, recall, and F1-score. These findings underscore that image preprocessing is an essential element of the CNN-based wrinkle detection framework, and that integrating CLAHE and sharpening is advised to improve the reliability of the wrinkle detection system.
Copyrights © 2026