Robust image identification without any visible information for double-compressed JPEG images

Robust Image Identification for Double-Compressed and Resized JPEG Images

“…a downloaded image. The JPEG standard is generally used as a lossy compression method, so several errors are caused in the generation process of double-compressed images [13], [19], as shown in Fig.2. In addition to "quantization error" in the encoding process, "rounding and truncation error" i.e.…”

“…IV, DC coefficients in the resized image can be calculated from ones in the image before resizing. • To determine parameters independently of the size of images The conventional scheme for double-compressed images [13], which uses not only DC but also AC coefficients, requires the setting of the parameter related to the size of identified images. On the other hand, the parameters used in the proposed scheme, i.e.…”

“…The proposed scheme was compared with two compressionmethod-dependent-schemes (zero positions-based scheme [13] and DC signs-based scheme [8]) and three image hashingbased schemes (low-rank and sparse decomposition-based scheme [15], quaternion-based one [16] and iterative quantization (ITQ)-based one [17]), where ITQ-based hash values were generated from 512 dimensional GIST feature vectors and each hash value was represented by 512 bits. In the schemes [15]- [17], the hamming distances between the hash value of a query image and those of all images in each database were calculated, and then images that had the smallest distance were chosen as the images generated from the same original image as the query, after decompressing all images.…”

“…On the other hand, due to the use of robust features against JPEG errors, compression-method-dependent schemes [7]- [13] have the stronger robustness than the first type ones. The schemes [7]- [10] use positive and negative signs of discrete cosine transform (DCT) coefficients, and the schemes [11]- [13] focus on the positions in which DCT coefficients have zero values. However, the identification for images having different sizes can not be performed.…”

Robust Image Identification with DC Coefficients for Double-Compressed JPEG Images

“…On the other hand, due to the use of robust features against JPEG errors, compression-method-dependent schemes [7]- [11] have the stronger robustness than the first type ones. The schemes [7], [8] use positive and negative signs of discrete cosine transform (DCT) coefficients, and the scheme [9]- [11] focuses on the positions in which DCT coefficients have zero values. They guarantee that there are no false negative matches for the identification between single-compressed images.…”