Several fragile watermarking schemes presented in the literature are either vulnerable to vector quantization (VQ) counterfeiting attacks or sacrifice localization accuracy to improve security. Using a hierarchical structure, we propose a method that thwarts the VQ attack while sustaining the superior localization properties of blockwise independent watermarking methods. In particular, we propo...

To achieve a better trade-off between the vector dimension and the memory requirements of a vector quantizer (VQ), an entropy-constrained VQ (ECVQ) scheme with finite memory, called finite-state ECVQ (FS-ECVQ), is presented in this paper. The scheme consists of a finite-state VQ (FSVQ) and multiple component ECVQs. By utilizing the FSVQ, the inter-frame dependencies within source sequence can b...

Compressive sensing (CS) provides a mathematical framework for utilizing the potentiality of sparse nature of the commonly used signals and has been the subject of scientific research in recent years. CS involves the compression of the data at the first step of image acquisition. This paper presents an image compression algorithm based on DCT based CS and Vector Quantization (VQ). It has been o...

In this paper, a hybrid watermarking scheme, that employs both DCT and VQ, has been presented. The authors have proposed a modification of the conventional LBG algorithm in this paper for designing the codebook to be used subsequently for compressing the image employing VQ. The watermark/logo is embedded in the constructed codebook after suitable DCT operations. The compression and reconstructi...

Objective(s): To review the findings of the patients with Sjögren’s syndrome (SS) having technetium-99m-pertechnetate (99mTc-pertechnetate) and gallium-67 citrate (Ga-67) salivary gland scintigraphy in the past eight years.Methods: The patients with SS, who were referred to our department for salivary gland scintigraphy during January 2008-December 2015 were studied using both 99mTc-pertechneta...

In this paper combined source-channel coding is considered for the case of predictive vector quantization. A design algorithm for channel optimized predictive vector quantizers is proposed. Under reasonable assumptions, the optimal encoder is presented and a sample iterative design method that simultaneously optimizes the predictor and the codebook is derived. We also demonstrate that this desi...

In this work we further evaluate a recently published, novel vector quantization (VQ) design for discrete HMM-based on-line handwriting recognition of whiteboard notes. To decorrelate the features, a principal component analysis (PCA) is applied. The novel VQ design ensures a lossless representation of the pressure information while modeling the statistical dependencies between the pressure and...

Conventional pixelwise classi cation techniques have two drawbacks. The rst is that they tend to occur isolated misclassi cations because they classify each site independently using spectral information only. The second is that sample data which represent each class are indispensable to estimate model parameters or to train classi cation Neural Networks. In this manuscript a new unsupervised co...

Scalar quantization is often preferred to vector quantization (VQ) for lossy data compression due to VQ significant encoding complexity. Specifically, the most time consuming task in VQ is the nearest neighbor search, involving numerous distortion calculations. Two main approaches can be considered for VQ complexity reduction. In the first one, complexity reduction is obtained by applying const...

Proof. Consider operators of the form A ©1#jl where A7 is a finite dimensional subspace of H, A is an operator on N with ||.4]| Sil, and lif± is the identity on NL. Such operators are clearly dense in (B in the strong operator topology, and Z7©ljvx is unitary if U is unitary on N. Therefore it is enough to prove (1) for finite dimensional spaces. In that case (1) follows from work of Bochner [l...