In recent years, the proliferation of digital image manipulation tools has made it easier for individuals with malicious intent to forge images. Copy-move forgery (CMF) is a common technique used in image tampering. Copy-move forgery detection (CMFD) is essential in various fields, including digital forensics, journalism, and law enforcement, as it helps ensure the integrity of digital images by identifying and mitigating attempts to manipulate them for deceptive purposes. Consequently, there is a pressing need for robust and efficient copy-move forgery detection methods. This evaluation provides a comprehensive assessment of the performance of these key-point-based algorithms in detecting copy-move forgeries. This work assesses the performance of the four State-of-the-art SIFT, SURF, BRISK and ORB algorithms on CoMoFoD dataset in terms of accuracy, precision, recall and f1-score.