Sharif Digital Repository

In this paper, new vector quantization (VQ) based techniques for reducing the effect of channel noise in image transmission are introduced. In one of the proposed methods, i.e., component VQ (CVQ), by transmitting the components of code-vectors (and not their indices), we will be able to reduce the effect of channel noise. To decrease the output rate of CVQ, a modification of CVQ called sub-index VQ (SIVQ) is introduced. This method has error-correcting capability as well. Simulation results show that CVQ and SIVQ techniques are robust to channel errors and surpass the conventional method, in which the indices of the selected code-vectors are protected using a Reed-Solomon code. An error... 

A novel compression algorithm for fingerprint images is introduced. Using wavelet packets and lattice vector quantization, a new vector quantization scheme based on an accurate model for the distribution of the wavelet coefficients is presented. The model is based on the generalized Gaussian distribution. We also discuss a new method for determining the largest radius of the lattice used and its scaling factor, for both uniform and piecewise-uniform pyramidal lattices. The proposed algorithms aim at achieving the best rate-distortion function by adapting to the characteristics of the subimages. In the proposed optimization algorithm, no assumptions about the lattice parameters are made, and... 

The current double JPEG compression detection techniques identify whether or not an JPEG image file has undergone the compression twice, by knowing its embedded quantization table. This paper addresses another forensic scenario in which the quantization table of a JPEG file is not explicitly or reliably known, which may compel the forensic analyst to blindly reveal the recompression clues. To do this, we first statistically analyze the theory behind quantized alternating current (AC) modes in JPEG compression and show that the number of quantized AC modes required to detect double compression is a function of both the image’s block texture and the compression’s quality level in a fresh... 

This paper presents a shape prediction algorithm in a noisy video sequence based on pixel representation in the undecimated wavelet domain. In our algorithm for tracking of user-defined shapes in a noisy sequence of images, the amplitude of coefficients in the best basis tree expansion of the undecimated wavelet packet transform are used as feature vectors (FVs). FVs robustness against noise has been achieved through inherent denoising and edge component separation in the best basis selection algorithm. The algorithm uses these FVs to track the pixels of small square blocks located at the vicinity of the object boundary. Searching for the best-matched block has been performed using... 

A well known method to reduce the intrinsic complexity of Multiple Input Multiple Output (MIMO) systems is to choose a subset of available antennas which have stronger links than the others, in order to perform the specified MIMO algorithm. The data resulted from the antenna selection process (at the receiver side) is sent back to the transmitter side via a feedback channel. There seems to be a need to reduce the number of feedack bits, specially when the number of antennas is not small. In this paper, we investigate the problem of reducing the number of feedback bits in antenna selection techniques. We've proposed two methods using vector quantization techniques to perform feedback bit... 

In content based image retrieval similarity measurement is one of the most important aspects in a large image database for efficient search and retrieval to find the best answer for a user query. Color and texture are among the more expressive of the visual features. Considerable work has been done in designing efficient descriptors for these features for applications such as similarity retrieval. The MPEG-7 specifies a standard set of descriptors for color, texture and shape. In the Human Vision System (HVS), visual information is not perceived equally; some information may be more important than other information. The purpose of this paper is to show how the MPEG-7 descriptor based on... 

This paper describes a vector quantization of a 600 bps speech coding parameters based on the Mixed Excitation Linear Prediction (MELP) model, which was accepted as a standard in communication on narrow-band HF channels. The MELP speech coders are robust in difficult background noise environments and intended mostly for military communications. To reduce the bit rate, a joint vector quantization of multi-frame is developed that takes advantage of inherent inter-frame redundancy of the MELP parameters. By grouping parameters of 4 frames into a multi-frame and using vector quantization, bit rate is decreased 4 times and output speech is still intelligible  

Fragile data hiding has been extensively used for secure transmission of the sensitive data using cover images, audios and videos. In the past decade, increasingly the remote sensing applications require transmission and archiving of large number of aerial images and videos. Storage and processing of remote sensing data in the public cloud computing and storage platforms, with servers outside the control of the data owners, requires sufficient attention to persevering the privacy of the data. Furthermore, in the past few years the applications of drones and unmanned aerial vehicles demand algorithms designed especially for low altitude remote sensing data. In this paper, a novel fragile data... 

A new methodology is proposed in this paper to both monitor an overall mean shift and classify the states of a multivariate quality control system. Based on the Bayesian rule (Montgomery, Introduction to statistical quality control, 5th edn. Wiley, New York, USA, 2005), the belief that each quality characteristic is in an out-of-control state is first updated in an iterative approach and the proof of its convergence is given. Next, the decision-making process of the detection and classification the process mean shift is modeled. Numerical examples by simulation are provided in order to understand the proposed methodology and to evaluate its performance. Moreover, the in-control and... 

Fragile data hiding has been extensively used for secure transmission of the sensitive data using cover images, audios and videos. In the past decade, increasingly the remote sensing applications require transmission and archiving of large number of aerial images and videos. Storage and processing of remote sensing data in the public cloud computing and storage platforms, with servers outside the control of the data owners, requires sufficient attention to persevering the privacy of the data. Furthermore, in the past few years the applications of drones and unmanned aerial vehicles demand algorithms designed especially for low altitude remote sensing data. In this paper, a novel fragile data... 

It is of fundamental importance to find algorithms obtaining optimal performance for learning of statistical models in distributed and communication limited systems. Aiming at characterizing the optimal strategies, we consider learning of Gaussian Processes (GP) in distributed systems as a pivotal example. We first address a very basic problem: how many bits are required to estimate the inner-products of some Gaussian vectors across distributed machines? Using information theoretic bounds, we obtain an optimal solution for the problem which is based on vector quantization. Two suboptimal and more practical schemes are also presented as substitutes for the vector quantization scheme. In... 

The learning vector quantization (LVQ) neural network is a useful tool for pattern recognition. Based on the network weights obtained from the training set, prediction can be made for the unknown objects. In this paper, discrimination of wines based on 2D NMR spectra is performed using LVQ neural networks with orthogonal signal correction (OSC). OSC has been proposed as a data preprocessing method that removes from X information not correlated to Y. Moreover, the partial least squares discriminant analysis (PLS-DA) method has also been used to treat the same data set. It has been found that the OSC-LVQ neural networks method gives slightly better prediction results than OSC-PLS-DA © 2005... 

An improved wavelet-based 2-D ECG data compression method is presented which employs a double stage compression. In the first stage the set partitioning in hierarchical trees (SPIHT) algorithm is used to compress the 2-D data array formed by cutting and beat-aligning the heartbeat data sequence. In the second stage vector quantization is applied to the residual image obtained from the previous stage. The 2-D approach utilizes both inter-beat and inter-sample redundancies in the ECG signal The proposed algorithm is applied to several records in the MIT-BIH arrhythmia database. Results show lower Percent Root mean square Difference (PRD) than 1-D methods and several 2-D methods for the same...