GPU-Based Fast Image Copy Detection

To speed up image copy detection by exploring the powerful computing capability of GPU,a novel GPU-based image copy detection scheme is proposed.Firstly,a new scale-invariant interest point detector-Harris-Hessian(H-H) is designed according to the architecture of GPU.The H-H extracts interest points in low scale and refines their location and scale in a series of scale-space with the determinant of Hessian matrix,which significantly reduces the pixel-level computation complexity and has better parallelism.Then,an image copy detection system based on the H-H is presented,the detection speed is significantly improved.The experimental results show that,compared to the existing CPU-based methods,the H-H achieves up to a speedup factor of 10~20 times and maintains a high detection accuracy.It only takes 19.8 ms for the system to detect a 640×480 image in a dataset of 11 250 images with 95% accuracy rate,which meets the demand of real-time applications under large scale data.