In this paper, we propose a novel technique that uses fingerprint features with coordinates (x, y), angle and type of feature as watermark information for authentication in H.264/AVC video. We utilize some techniques such as Gabor algorithm, locally adaptive thresholding, and Hilditch's thinning together with heuristic rules and Hamming measurement to optimally extract minutiae vector (x, y, angle, type) from fingerprint as well as to improve accuracy of matching process. Furthermore, to make our scheme robust, the minutiae vector will be converted to binary stream which is increased three times and the lowest frequency of DCT blocks of transition images or frames in H.264 video is properly chosen to hold them. With our proposed technique, the authentication scheme can achieve high capacity and good quality. Experimental results show that our proposed technique is robust against to H.264 encoder, time stretching in video, Gaussian noise, adding blur, frame removal in video, and cutting some regions in the frame of video.