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A robust image hash function based on color and texture features of the image

机译:基于图像颜色和纹理特征的强大图像哈希函数

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As the internet grows, the amounts of digital data like images generated by the users are increasing in huge amount. Thus a mechanism is needed to manage large database and at the same time provide protection, verification, integrity and authentication of data. An image hash function is one such mechanism. It takes an image data as an input and produces a value of foxed size as output. The main aim of this paper is to develop a robust hash function which can withstand legitimate modification. A robust hash function based on Discrete Cosine Transformation (DCT) and local variations in the Gray Level Cooccurence Matrix (GLCM) is being proposed in this paper. The image is partitioned into several rings before extracting the image features which makes it more robust to rotation attack which is not robust to most of the existing hash functions. The experimental result shows that the proposed method is robust against various geometrical methods.
机译:随着互联网的增长,用户生成的数字数据的数量以大量的数量增加。因此,需要一种机制来管理大型数据库,同时提供数据的保护,验证,完整性和认证。图像哈希函数是一种这样的机制。它将图像数据作为输入,并产生狐型大小的值作为输出。本文的主要目的是开发一种能够承受合法修改的强大散列功能。本文提出了一种基于离散余弦变换(DCT)和灰级共同矩阵(GLCM)的局部变型的鲁棒哈希函数。在提取图像特征之前,图像被划分为多个环,这使得对旋转攻击更加坚固,这对大多数现有散列函数不稳健。实验结果表明,该方法对各种几何方法具有鲁棒性。

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