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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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摘要

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:随着互联网的发展,诸如用户生成的图像之类的数字数据量正在大量增加。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。图像哈希函数就是这样一种机制。它以图像数据作为输入,并生成foxed大小的值作为输出。本文的主要目的是开发一种可以承受合法修改的健壮哈希函数。本文提出了一种基于离散余弦变换(DCT)和灰度共生矩阵(GLCM)的局部变化的鲁棒哈希函数。在提取图像特征之前,将图像划分为几个环,这使其对旋转攻击更健壮,而对大多数现有哈希函数而言则不健壮。实验结果表明,该方法对各种几何方法均具有较强的鲁棒性。

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