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A SIFT-based image fingerprinting approach robust to geometric transformations

机译:基于SIFT的图像指纹识别方法对几何变换具有鲁棒性

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Among approaches in implementing digital rights management, image fingerprinting technique is considered to be one of the most attractive solutions, especially in detecting illegal use of image works. The deficiency of the existing image fingerprinting methods is that they can not deal with geometric transformations, such as aspect ratio changes, rotations, cropping, combining, etc. Aiming at this shortcoming, we propose a SIFT-based image fingerprinting algorithm which is robust to geometric transformations. Firstly, we introduce SIFT-based algorithm to extract features as a unique fingerprint. Secondly, a method based on area ratio invariance of affine transformation is utilized to verify valid matched keypoint pairs between the queried image and the pre-registered image. Finally, by counting the valid matched pairs, we estimate whether the two images are homologous or not. Experimental results demonstrate that the proposed method exhibits an excellent performance when geometric transformation occurs.
机译:在实施数字版权管理的方法中,图像指纹技术被认为是最有吸引力的解决方案之一,尤其是在检测非法使用图像作品方面。现有图像指纹方法的不足之处在于不能处理长宽比变化,旋转,裁剪,组合等几何变换。针对这一缺点,我们提出了一种基于SIFT的图像指纹算法,该算法具有较强的鲁棒性。几何变换。首先,我们引入基于SIFT的算法来提取特征作为唯一指纹。其次,利用基于仿射变换的面积比不变性的方法来验证查询图像和预注册图像之间的有效匹配关键点对。最后,通过计算有效的匹配对,我们估计两个图像是否同源。实验结果表明,该方法在发生几何变换时表现出优异的性能。

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