Recent Submissions

  • A Novel Steganography Technique for SDTV-H.264/AVC Encoded Video

    Di Laura, Christian; Pajuelo, Diego; Kemper, Guillermo (Hindawi Publishing Corporation, 2016-04)
    Today, eavesdropping is becoming a common issue in the rapidly growing digital network and has foreseen the need for secret communication channels embedded in digital media. In this paper, a novel steganography technique designed for Standard Definition Digital Television (SDTV) H.264/AVC encoded video sequences is presented. The algorithm introduced here makes use of the compression properties of the Context Adaptive Variable Length Coding (CAVLC) entropy encoder to achieve a low complexity and real-time inserting method. The chosen scheme hides the private message directly in the H.264/AVC bit stream by modifying the AC frequency quantized residual luminance coefficients of intrapredicted I-frames. In order to avoid error propagation in adjacent blocks, an interlaced embedding strategy is applied. Likewise, the steganography technique proposed allows self-detection of the hidden message at the target destination. The code source was implemented by mixing MATLAB 2010 b and Java development environments. Finally, experimental results have been assessed through objective and subjective quality measures and reveal that less visible artifacts are produced with the technique proposed by reaching PSNR values above 40.0 dB and an embedding bit rate average per secret communication channel of 425 bits/sec. This exemplifies that steganography is affordable in digital television.
  • A biometric method based on the matching of dilated and skeletonized IR images of the veins map of the dorsum of the hand

    Universidad Peruana de Ciencias Aplicadas (UPC) (IEEE, 2015-06-02)
    This work proposes a biometric identification system that works together with a palm vein reader sensor and a hand-clenching support, designed to perform the capture the back of the hand. Several processing steps were performed: extraction of the region of interest, binarization, dilation, noise filtering, skeletonization, as well as extraction and verification of patterns based on the measurment of coincidence of vertical and horizontal displacements of skeletonized and dilated images. The proposed method achieved the following results: processing time post capture of 1.8 seconds, FRR of 0.47% and FAR of 0,00%, with a referential database of 50 people from a total of 1500 random captures.