Image hashing using AQ-CSLBP with double bit quantization

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.