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Image hashing using AQ-CSLBP with double bit quantization

机译:使用AQ-CSLBP和双比特量化的图像哈希

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This paper presents a novel image hashing method for authentication and tampering detection. Creation, modification and transfer of multimedia data becomes an easy task due to digitization. Integrity is very important for crucial and sensitive matters like medical records, legal matters, scientific research, forensic investigations and government documents. Image hashing is one of the popular method to maintain integrity of image. We proposed AQ-CSLBP (Average Compressed Center Symmetric Local Binary Pattern) as a feature descriptor for image hashing. First, image is divided into sub blocks, AQ-CSLBP is applied on each sub block to generate 8 bin histogram as a feature. Then, we used double bit quantization to generate hash code for the image. The proposed method is compared with the existing methods by way of quantitative analysis, it has been proved that the proposed method works well in authentication scenario with less hash length and more discrimination power.
机译:本文提出了一种新的用于认证和篡改检测的图像哈希方法。由于数字化,多媒体数据的创建,修改和传输变得很容易。对于医疗记录,法律事务,科学研究,法医调查和政府文件之类的关键和敏感事务,诚信至关重要。图像哈希是保持图像完整性的流行方法之一。我们提出了AQ-CSLBP(平均压缩中心对称局部二进制模式)作为图像哈希的特征描述符。首先,将图像划分为子块,将AQ-CSLBP应用于每个子块,以生成8 bin直方图作为特征。然后,我们使用双位量化为图像生成哈希码。通过定量分析与现有方法进行了比较,证明了该方法在哈希长度较小,鉴别力较大的认证场景下效果良好。

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