doi:

DOI: 10.3724/SP.J.1089.2010.11041

Journal of Computer-Aided Design & Computer Graphics (计算机辅助设计与图形学学报) 2010/22:9 PP.1483-1490

GPU-Based Fast Image Copy Detection


Abstract:
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.

Key words:image copy detection,scale invariant,interest points,GPU,CUDA

ReleaseDate:2014-07-21 15:25:43



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