Efficient Hashing Method Using 2D-2D PCA for Image Copy Detection

Image copy detection is an important technology of copyright protection. This paper proposes efficient hashing method for image using 2D-2D (two-directional two-dimensional) PCA (Principal Component Analysis). The key the discovery translation invariance PCA. With property invariance, a novel model extracting rotation-invariant low-dimensional features designed by combining PCT (Polar Coordinate Transformation) and can convert input rotated to matrix. Since invariant translation, learned from matrix are rotation-invariant. Moreover, vector distances stable common digital operations thus hash construction with robustness compactness. Three open datasets exploited conduct various experiments validating efficiencies proposed method. results demonstrate that much better than some representative methods in performances classification detection.