Digital images are widely distributed today over the internet and through other mediums. There are powerful digital image processing tools which have made perfect image duplication a trivial procedure. Therefore, security, copyright protection, and integrity verification of digital video have become an urgent issue in the digital world, which can be achieved by means of a technique called digital watermarking. The issues of watermarking are to achieve imperceptibility, robustness, payload and security simultaneously. This paper presents a new Quaternion Curvelet Transform (QCT) based video watermarking technique for embedding a video on another video in a secure and optimized way. However, many of the existing techniques are unable to handle the problem of rotation, translation and scaling attacks on watermarked video. This study presents a novel embedding approach where in the quaternion transform followed by the traditional Curvelet transform is able to overcome the above disadvantages. In this paper, we first represent the color cover video frames in the quaternion form and subsequently generate Quaternion Curvelet Transform (QCT) coefficients for each such quaternion frames. Second, in order to withstand the desynchronization causes due to the geometrical attacks, the Harris corner detection algorithm is used to determine the invariant feature points on the QCT coefficients, which is followed by the calculation of energy for each block centered on those feature points. Third, in order to maintain the trade-off among the watermarking characteristics, the optimized location for embedding the watermark frames is determined using the cuckoo search optimization algorithm. Finally, to attain the authenticity, an authentication key generation procedure is employed using the owner’s biometric image and the watermarked frames. The experimental results prove that the proposed method is promising in terms of robustness, imperceptibility and security to most notable image processing attacks, geometrical attacks, and video processing attacks among the various conventional watermarking algorithms. © 2018, Springer Science+Business Media, LLC, part of Springer Nature.