Robust blind watermarking approach against the compression for fingerprint image using 2D-DCT - Lebcir, Mohamed; Suryanti, Awang; Benziane, Ali (Springer US, 2022)
This article presents a recent blind and robust fingerprint image watermarking scheme based on a two-dimensional discrete cosine transform (2D-DCT). The main focus is to compress the fingerprint image watermarked data for the purpose of reducing the volume of storage or sending over the network. The fingerprint features might be affected by the embedded watermark, compression of fingerprint images and the sending across network, thereby leading to various sets of features or watermark data. In order to address this goal in a differential way, the watermark sequence bit two sub-vectors were utilized. The two sub-vectors were achieved by the two-dimensional discrete cosine transform of the host image. Throughout the extraction stage, the essential distinction between the corresponding sub-vectors of the watermarked fingerprint image resulted explicitly in an embedded watermark sequence. The advantage of the proposed method is that it can develop a new simple blind and robust watermarking scheme by 2D-DCT frequency domain on the whole image. Accomplished results relative to other reliable compression schemes showed that the proposed scheme has greater or equivalent robustness to common image processing and geometric attacks, such as cropping, resizing, and rotation. To extract watermark data, the initial fingerprint image was not necessary. The proposed study was tested using 80 fingerprint images from 10 persons, for each from CASIA-FingerprintV5 and FVC2002 fingerprint databases. Eight fingerprint images for each individual were set as the format at which the watermark was embedded in each one.