Use of SHDM in commutative watermarking encryption

SHDM stands for Sphere-Hardening Dither Modulation and is a watermarking algorithm based on quantizing the norm of a vector extracted from the cover work. We show how SHDM can be integrated into a fully commutative watermarking-encryption scheme and investigate implementations in the spatial, DCT, and DWT domain with respect to their fidelity, robustness, capacity, and security of encryption. The watermarking scheme, when applied in the DCT or DWT domain, proves to be very robust against JPEG/JPEG2000 compression. On the other hand, the spatial domain-based approach offers a large capacity. The increased robustness of the watermarking schemes, however, comes at the cost of rather weak encryption primitives, making the proposed CWE scheme suited for low to medium security applications with high robustness requirements.

Quantitative Assessment of the Effects of Compression on Deep Learning in Digital Pathology Image Analysis

PURPOSE Deep learning (DL), a class of approaches involving self-learned discriminative features, is increasingly being applied to digital pathology (DP) images for tasks such as disease identification and segmentation of tissue primitives (eg, nuclei, glands, lymphocytes). One application of DP is in telepathology, which involves digitally transmitting DP slides over the Internet for secondary diagnosis by an expert at a remote location. Unfortunately, the places benefiting most from telepathology often have poor Internet quality, resulting in prohibitive transmission times of DP images. Image compression may help, but the degree to which image compression affects performance of DL algorithms has been largely unexplored. METHODS We investigated the effects of image compression on the performance of DL strategies in the context of 3 representative use cases involving segmentation of nuclei (n = 137), segmentation of lymph node metastasis (n = 380), and lymphocyte detection (n = 100). For each use case, test images at various levels of compression (JPEG compression quality score ranging from 1-100 and JPEG2000 compression peak signal-to-noise ratio ranging from 18-100 dB) were evaluated by a DL classifier. Performance metrics including F1 score and area under the receiver operating characteristic curve were computed at the various compression levels. RESULTS Our results suggest that DP images can be compressed by 85% while still maintaining the performance of the DL algorithms at 95% of what is achievable without any compression. Interestingly, the maximum compression level sustainable by DL algorithms is similar to where pathologists also reported difficulties in providing accurate interpretations. CONCLUSION Our findings seem to suggest that in low-resource settings, DP images can be significantly compressed before transmission for DL-based telepathology applications.

An FPGA Accelerator for Real-Time Lossy Compression of Hyperspectral Images

Hyperspectral images offer great possibilities for remote studies, but can be difficult to manage due to their size. Compression helps with storage and transmission, and many efforts have been made towards standardizing compression algorithms, especially in the lossless and near-lossless domains. For long term storage, lossy compression is also of interest, but its complexity has kept it away from real-time performance. In this paper, JYPEC, a lossy hyperspectral compression algorithm that combines PCA and JPEG2000, is accelerated using an FPGA. A tier 1 coder (a key step and the most time-consuming in JPEG2000 compression) was implemented in a heavily pipelined fashion. Results showed a performance comparable to that of existing 0.18 μm CMOS implementations, all while keeping a small footprint on FPGA resources. This enabled the acceleration of the most complex step of JYPEC, bringing the total execution time below the real-time constraint.

Use of SHDM in Commutative Watermarking-Encryption

SHDM stands for Sphere Hardening Dither Modulation and is a watermarking algorithm based on quantizing the norm of a vector extracted from the cover work. We show how SHDM can be integrated into a fully commutative watermarking encryption scheme and investigate implementations in the spatial, DCT- and DWT-domain with respect to their delity, robustness, capacity and security of encryption. The watermarking scheme, when applied in the DCT- or DWT-domain, proves to be very robust against JPEG/JPEG2000 compression. On the other hand, the spatial domain-based approach offers a large capacity. The increased robustness of the watermarking schemes, however, comes at the cost of rather weak encryption primitives, making the proposed CWE scheme suited for low - medium security applications with high robustness requirements.

Multiple watermarking technique using optimal threshold

<span>The multiple watermarking technique has drawn more attention due to high demand for embedding more than one copyright. This paper proposes a multiple watermarking scheme using DWT-SVD by utilizing HVS characteristics. Our scheme embeds multiple watermarks in red and blue colors. The proposed scheme examines the coefficients of U orthogonal matrix for embedding and extracting watermarks. Watermarks are scrambled by Arnold transform before embedded in the host image in order provide additional security. The optimal thresholds for red and blue colors are revealed by finding a trade-off between normalized-cross correlation and imperceptibility from quantization steps. The experimental results demonstrate that our scheme achieves high resistant under JPEG and JPEG2000 compression for both inserted watermarks. </span>

Entropy-Based Semi-Fragile Watermarking of Remote Sensing Images in the Wavelet Domain

This article presents a semi-fragile image tampering detection method for multi-band images. In the proposed scheme, a mark is embedded into remote sensing images, which have multiple frequential values for each pixel, applying tree-structured vector quantization. The mark is not embedded into each frequency band separately, but all the spectral values (known as signature) are used. The mark is embedded in the signature as a means to detect if the original image has been forged. The image is partitioned into three-dimensional blocks with varying sizes. The size of these blocks and the embedded mark is determined by the entropy of each region. The image blocks contain areas that have similar pixel values and represent smooth regions in multispectral or hyperspectral images. Each block is first transformed using the discrete wavelet transform. Then, a tree-structured vector quantizer (TSVQ) is constructed from the low-frequency region of each block. An iterative algorithm is applied to the generated trees until the resulting tree fulfils a requisite criterion. More precisely, the TSVQ tree that matches a particular value of entropy and provides a near-optimal value according to Shannon’s rate-distortion function is selected. The proposed method is shown to be able to preserve the embedded mark under lossy compression (above a given threshold) but, at the same time, it detects possibly forged blocks and their positions in the whole image. Experimental results show how the scheme can be applied to detect forgery attacks, and JPEG2000 compression of the images can be applied without removing the authentication mark. The scheme is also compared to other works in the literature.

Identification of a Standardized Automobile Bio-metric Security System based on Accuracy and Response time: Applicable for the Indian Automobile Market

This paper aims at the identification of a standard security system for commercial and personal vehicles installed on a remote-controlled unlocking device that promises a high accuracy without compromising on the response time. The proposed technology combines three bio-metric security systems on the basis of their performance and response times to make vehicles more secured. The paper compares the efficiencies of different bio-metric security systems based upon their mean accuracy and response times. Primary data have been collected using existing devices and technology, a detailed statistical comparison is done using computational tools like IBM SPSS 2.0 and Microsoft Excel using statistical concepts like ANOVA, Square of means, Descriptive statistics, Central tendencies, etc. The hardware required for this proposed security system is already available at reasonable cost and can be implemented in the field of automobile and a standard security system can be identified for use across all variants of vehicles universally for all the manufacturers. The performance of the bio-metric devices was measured using a 16-megapixel Sony camera IMX371 Exmor RS sensor with a pixel size of 1.0 micro-meter, mounted on a OnePlus 5T mobile phone for face recognition and a fingerprint sensor with a claimed unlock speed of 0.2 seconds mounted on the same device. Mantra MI S100 single iris scanner was used with a high-resolution sensor (CMOS) and captures images with a JPEG2000 compression format.