Application of passive terahertz imaging in concealed weapon detection has been looked at, such that the final result is the segmentation of the foreground concealed weapons from the rest of the background. For the same, a fully automatic and completely generic technique, without any learning, has been proposed. It was observed that a simple thresholding step, exploiting varied intensity bands of the tetrahertz images is not enough. Thus, an innovative method to isolate humans and thus improve the region of interest (ROI) has been proposed. Thereafter, saliency has been used to further improve ROI, as these images are quite noisy and the central focusing aspect of saliency could handle the noise around the concealed weapons. It was observed that this step could handle the noise around the concealed weapons but degraded the boundaries of the concealed weapons. To further improve boundary adherence, superpixels are used. Finally, results are evaluated both quantitatively and qualitatively and outperformed the traditional approach.
In this paper, a robust watermarking technique based on fractional cosine transform and singular value decomposition
is presented to improve the protection of the images. A meaningful gray scale image is used as watermark
instead of randomly generated Gaussian noise type watermark. First, host image is transformed by the means
of fractional cosine transform. Now, the positions of all frequency coefficients are changed with respect to some
rule and this rule is secret and only known to the owner/creator. Then inverse fractional cosine transform is
performed to get the reference image. Watermark logo is embedded in the reference image by modifying its
singular values. For embedding, the singular values of the reference image are found and then modify it by
adding the singular values of the watermark image. A reliable watermark extraction algorithm is developed for
extracting watermark from possibly attacked image. The experimental results show better visual imperceptibility
and resiliency of the proposed scheme against intentional or un-intentional variety of attacks.
KEYWORDS: Digital watermarking, Image compression, Image processing, Digital imaging, 3D image processing, 3D vision, Image transmission, Image filtering, Digital filtering, Information security
We present a robust stereo-image coding algorithm using digital watermarking in fractional Fourier transform (FrFT) and singular value decomposition (SVD). For the purpose of the security, the original (left stereo) image has been degraded and watermark (right disparity map) is embedded in the degraded image. This watermarked degraded stereo image is processed in an insecure channel. At the receiver's end, both the watermarked image (left stereo image) and watermark images are found by the decoding process. The use of the FrFT, SVD, and degradation process of the stereo image add much more complexity to decode the information about the stereo images and disparity map extraction. Moreover, processing of the watermarked image only provides the stereo as well as 3-D information of the scene/object. Experimental results show that the proposed algorithm is efficient to achieve stereo image security.
In this paper, a multipurpose watermarking scheme is proposed. The meaning of the word multipurpose is to make the proposed scheme as single watermarking scheme (SWS) or multiple watermarking scheme (MWS)
according to our requirement and convenience. We first segment the host image into blocks by means of Hilbert space filling curve and based on amount of DCT energy in the blocks, the threshold values are selected which make proposed scheme multipurpose. For embedding of n watermarks (n - 1) thresholds are selected. If the
amount of DCT energy of the block is less than the threshold value then ENOPV decomposition is performed and watermark is embedded in either low or high or all frequency sub-bands by modifying the singular values. If the amount of DCT energy of the block is greater than the threshold value then embedding is done by modifying
the singular values. This process of embedding through ENOPV-SVD and SVD is applied alternatively to all (n - 1) threshold values. Finally, modified blocks are mapped back to their original positions using inverse Hilbert space filling curve to get the watermarked image. A reliable extraction process is developed for extracting all
watermarks from attacked image. Experiments are done on different standard gray scale images and robustness is carried out by a variety of attacks.
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