This paper proposes a fingerprint method for webtoon identification using frequency features. The proposed fingerprint method uses features of a webtoon extracted from frequency components of each row of the webtoon image. Applying the proposed fingerprint method, the perfect accuracy is achieved for webtoon identification with randomly selected webtoon patches for testing. We compared our proposed method with a global thresholding method in frequency domain. Simulation results show that our method gets 100% accuracy with distorted (JPEG compression) images while the global thresholding method gets 32% accuracy only.