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Image hashing using AQ-CSLBP with double bit quantization

机译:使用AQ-CSLBP具有双比特量化的图像散列

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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:本文提出了一种用于认证和篡改检测的新型图像散列方法。由于数字化,多媒体数据的创建,修改和传输成为一项简单的任务。诚信对于医疗记录,法律事务,科学研究,法医调查和政府文件等关键和敏感事项非常重要。图像散列是维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)作为图像散列的特征描述符。首先,将图像分成子块,AQ-CSLBP应用于每个子块以生成8个BIN直方图作为特征。然后,我们使用双比特量化来为图像生成散列码。通过定量分析将所提出的方法与现有方法进行比较,已经证明了所提出的方法在认证场景中运行较少,具有较少的散列长度和更多辨别力。

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