［Objective］ To address the issues of traditional biofouling evaluation，such as difficulty in quantification，low efficiency，and strong subjectivity，an automated quantitative evaluation scheme based on image recognition technology was proposed.［Methods］ A seven-month marine immersion test was conducted in the waters of Liuheng Island，Zhoushan. We fully documented the biofouling progression on three types of test panels，covering the period from the off-season to the peak season of fouling organism growth. The biofouling images were analyzed and compared using the quadrat method，the annotation masking method and the image recognition method，and an enhanced fouling rating evaluation model was established.［Results］The U-Net model achieved high recognition accuracy for biofouling images，and its recognition speed was two orders of magnitude faster than manual methods，requiring only 71. 6 ms per image. By introducing species-specific weighting coefficients，a fouling rating evaluation model was proposed. From June to September，the fouling ratingof blank panel increased from 15. 5 to 157. 4. Hydrolytic coating A exhibited a lower fouling rating and superior anti-fouling performance than self-polishing coating B，indicating that the anti-foulingefficacy of coatings differed under different actual marine conditions.［Conclusion］Image recognitiontechnology provided an efficient and reliable technical means for the quantitative assessment of marinebiofouling and the evaluation of anti-fouling coating performance，and significantly improved the accuracy and rationality of fouling evaluation.