We propose a method for reducing the size of a share in visual secret sharing schemes. The proposed method does not cause the leakage and the loss of the original image. The quality of the recovered image is almost same as that of previous schemes.

A novel thresholding algorithm for change detection in video sequences is proposed. The method is based on image differencing and the intensity distribution of a difference image. With a difference image between two consecutive images, we prepare a new image model for the distribution of stationary pixels. The distribution of moving pixels is then separated by extracting the distribution of stationary pixels from the overall distribution of the difference image. Pixels that exhibit a significant change in intensity are classified using a likelihood criterion. The proposed algorithm is tested on the standard MPEG sequences and verified to have reliable performance.

We present a speaker adaptation method that makes it possible to determine articulatory parameters from an unknown speaker's speech spectrum using an HMM (Hidden Markov Model)-based speech production model. The model consists of HMMs of articulatory parameters for each phoneme and an articulatory-to-acoustic mapping that transforms the articulatory parameters into a speech spectrum for each HMM state. The model is statistically constructed by using actual articulatory-acoustic data. In the adaptation method, geometrical differences in the vocal tract as well as the articulatory behavior in the reference model are statistically adjusted to an unknown speaker. First, the articulatory parameters are estimated from an unknown speaker's speech spectrum using the reference model. Secondly, the articulatory-to-acoustic mapping is adjusted by maximizing the output probability of the acoustic parameters for the estimated articulatory parameters of the unknown speaker. With the adaptation method, the RMS error between the estimated articulatory parameters and the observed ones is 1.65 mm. The improvement rate over the speaker independent model is 56.1 %.

In this paper, we present a predictive control method, based on Fuzzy Neural Network (FNN), for the control of chaotic systems without precise mathematical models. In our design method, the parameters of both predictor and controller are tuned by a simple gradient descent scheme, and the weight parameters of the FNN are determined adaptively throughout system operations. In order to design the predictive controller effectively, we describe the computing procedure for each of the two important parameters. In addition, we introduce a projection matrix for determining the control input, which decreases the control performance function very rapidly. Finally, we depict various computer simulations on two representative chaotic systems (the Duffing and Hénon systems) so as to demonstrate the effectiveness of the new chaos control method.

Cryptography and Coding Theory are closely related in many respects. Recently, the problem of "decoding Reed Solomon codes" (also known as "polynomial reconstruction") was suggested as an intractability assumption to base the security of protocols on. This has initiated a line of cryptographic research exploiting the rich algebraic structure of the problem and its variants. In this paper we give a short overview of the recent works in this area as well as list directions and open problems in Polynomial Reconstruction Based Cryptography.

This paper considers Quasi-Reduced ordered Multi-valued Decision Diagrams with k bits (QRMDD(k)s) to represent binary logic functions. Experimental results show relations between the values of k and the numbers of nodes, the memory sizes, the numbers of memory accesses, and area-time complexity for QRMDD(k). For many benchmark functions, the numbers of nodes and memory accesses for QRMDD(k)s are nearly equal to of the corresponding Quasi-Reduced ordered Binary Decision Diagrams (QRBDDs), and the memory sizes and the area-time complexities for QRMDD(k)s are minimum when k = 2 and k = 3-6, respectively.

In this paper, we propose a noise-robust automatic speech recognition system that uses orthogonalized distinctive phonetic features (DPFs) as input of HMM with diagonal covariance. In an orthogonalized DPF extraction stage, first, a speech signal is converted to acoustic features composed of local features (LFs) and ΔP, then a multilayer neural network (MLN) with 153 output units composed of context-dependent DPFs of a preceding context DPF vector, a current DPF vector, and a following context DPF vector maps the LFs to DPFs. Karhunen-Loeve transform (KLT) is then applied to orthogonalize each DPF vector in the context-dependent DPFs, using orthogonal bases calculated from a DPF vector that represents 38 Japanese phonemes. Each orthogonalized DPF vector is finally decorrelated one another by using Gram-Schmidt orthogonalization procedure. In experiments, after evaluating the parameters of the MLN input and output units in the DPF extractor, the orthogonalized DPFs are compared with original DPFs. The orthogonalized DPFs are then evaluated in comparison with a standard parameter set of MFCCs and dynamic features. Next, noise robustness is tested using four types of additive noise. The experimental results show that the use of the proposed orthogonalized DPFs can significantly reduce the error rate in an isolated spoken-word recognition task both with clean speech and with speech contaminated by additive noise. Furthermore, we achieved significant improvements when combining the orthogonalized DPFs with conventional static MFCCs and ΔP.

This paper proposes two alternative approaches that do not make use of a dictionary but instead utilizes different types of learned features to segment words in a language that has no explicit word boundary. Both methods utilize decision trees as knowledge representation acquired from a training corpus in the segmentation process. The first method, a language-dependent technique, applies a set of constructed features patterns based on character types to generate a set of heuristic segmentation rules. It separates a running text into a sequence of small chunks based on the given patterns, and constructs a decision tree for word segmentation. The second method extracts statistics of character sequences from a training corpus and uses them as features for the process of constructing a set of rules by decision tree induction. The latter needs no linguistic knowledge. By experiments on Thai language, both methods achieve relatively high accuracy but the latter performs much better.

Feature point tracking over a video sequence fails when the points go out of the field of view or behind other objects. In this paper, we extend such interrupted tracking by imposing the constraint that under the affine camera model all feature trajectories should be in an affine space. Our method consists of iterations for optimally extending the trajectories and for optimally estimating the affine space, coupled with an outlier removal process. Using real video images, we demonstrate that our method can restore a sufficient number of trajectories for detailed 3-D reconstruction.

In this letter, we propose a groupwise successive interference cancellation (GSIC) receiver with gradient descent search for multi-rate DS-CDMA system. Proposed receiver incorporates iterative gradient descent search algorithm into conventional GSIC receiver for multi-rate DS-CDMA system. It is shown that the receiver achieves significant performance improvement over the matched filter (MF) receiver, GSIC receiver, multi-stage parallel interference cacnellation (PIC) receiver, multi-stage partial PIC receiver, and GSIC receiver with PIC in a Rayleigh fading channel.

It is a critical design process to estimate the fractional errors of the Synthetic Aperture Radar (SAR) processor before implementation. The contribution of this paper is to identify the chief sources and types and to suggest an estimation technique for overall fractional errors of the space-based SAR processor using Range-Doppler Algorithm (RDA). Also, simulation is performed to the Experimental-SAR (E-SAR) processor to examine the practicability and efficiency of the technique, the results are discussed, and the solutions for problems are recommended. Therefore, this technique can be used to estimate the fractional errors of the space-based SAR processor using RDA.

Classical studies of Asynchronous Transfer Mode (ATM) switching elements and in particular the buffer behavior of the Shared Buffer Memory (SBM), assume that all read and write operations of cells to, respectively from, the SBM are executed simultaneously. However, in a real switching element, the inlets (outlets) are scanned sequentially for arriving (departing) cells during the so-called input (output) cycle. Furthermore, the input and output cycles are intermingled, each read operation being followed by a write operation. This is referred to as the Timeslot Interchange Mechanism (TIM). In this paper, we present the analysis of a queueing model that includes the TIM. We model the cell arrival processes on the inlets of the switching element as independent Bernoulli arrival processes. Moreover, we assume that cells are routed from the inlets to the outlets of the switching element according to an independent and uniform process, i.e., the destinations of consecutive cell arrivals on any given inlet are independent and for a given cell all destinations are equiprobable. Under these assumptions, we will derive expressions for the probability generating functions of the queue length in an individual routing group (a logical queue that contains all cells scheduled for the same destination), the (total) queue length in the SBM, and the cell waiting time. From these results, expressions for the mean values and the tail distributions of these quantities are calculated, and the influence of the TIM on the buffer behavior is studied through comparison with a model where all read and write operations occur simultaneously.

A major challenge in the design of multimedia networks is to meet the quality of service (QoS) requirements of all admitted users. Regulation and scheduling are key factors for fulfilling such requirements. We propose a rate-based regulation-scheduling scheme in which the regulation function is modulated by both the tagged stream's characteristics and the state information fed-back from the scheduler. The rate-jitter and bandwidth share of each tagged connection are controlled appropriately by considering the system time and the queue length of the scheduler. Simulation results have shown that the proposed scheme works better than other rate-based disciplines.

Although watermarking techniques have been extensively developed for natural videos, little progress is made in the area of graphics animation. Following the former successful MPEG-1 and MPEG-2 coding standards that provide efficient representations of natural videos, the emerging MPEG-4 standard incorporates new coding tools for 2D mesh animation. Graphics animation information is crucial for many applications and may need proper protection. In this paper, we develop a watermarking technique suitable for MPEG-4 2D mesh animation. The proposed method is based on the multiresolution analysis of 2D dynamic mesh. We perform wavelet transform on the temporal sequence of the node points to extract the significant spectral components of mesh movement, which we term the "feature motions. " A binary watermark invisibly resides in the feature motions based on the spread-spectrum principle. Before watermark detection, a spatial-domain least-squares registration technique is used to restore the possibly geometrically distorted mesh data. Each watermark bit is then detected by hard decision with cryptographically secure keys. We have tested the proposed method with a variety of attacks, including affine transformations, temporal smoothing, spectral enhancement and attenuation, additive random noise, and a combination of the above. Experimental results show that the proposed watermarks can withstand the aforementioned attacks.

In this paper, we introduce the following m-layered hard constrained convex feasibility problem HCF(m): Find a point u m, where 0:=H (a real Hilbert space), i: = arg min gi(i-1) and gi(u):=wi,jd 2(u,Ci,j) are defined for (i) nonempty closed convex sets Ci,jH and (ii) weights wi,j > 0 satisfying wi,j=1 (i {1,,m}, j {1,,Mi}. This problem is regarded as a natural extension of the standard convex feasibility problem: find a point u Ci, where Ci H (i {1,, M}) are closed convex sets. Unlike the standard problem, HCF(m) can handle the inconsistent case; i.e., i,j Ci,j = , which unfortunately arises in many signal processing, estimation and design problems. As an application of the hybrid steepest descent method for the asymptotically shrinking nonexpansive mapping, we present an algorithm, based on the use of the metric projections onto Ci,j, which generates a sequence (un) satisfying limn d(un,3) = 0 (for M1 = 1) when at least one of C1,1 or C2,j's is bounded and H is finite dimensional. An application of the proposed algorithm to the pulse shaping problem is given to demonstrate the great flexibility of the method.

This paper proposes an instruction-level power estimation method for an embedded RISC processor, the power consumption of which fluctuates so much by applications and input data. The proposed method estimates the power consumption from the result of ISS (Instruction Set Simulator) and energy tables according to Hamming Distance of Registers (HDR) of all instructions. It is over 105 times faster than the gate-level detailed logic simulation, while the estimated power curves have the same tendency with those from the logic simulation. The proposed method realizes both accurate and fast power estimation of embedded processors.

A scheme of error correction for JPEG2000 codestream is proposed in this paper. The scheme uses a forward error correction code (FEC) and a data hiding technique. The headers and the higher quality layers of the codestream are coded using FEC codes. Then the parity data are separated from the FEC-coded data and hidden in the JPEG2000 codestream. The hidden data are used for error correction at the decoder. Several error correction codes with different strength are selected for the main header, the tile-part headers, the packet headers, and the bodies. The codestream generated by the proposed scheme has backward compatibility with a standard JPEG2000 codestream. Thus, it can be decoded with a general decoder. Simulation results demonstrated the effectiveness of the proposed scheme.

The paper discusses the spatio-temporal phenomena in autonomous two-layer Cellular Neural Networks (CNNs) with mutually coupled templates between two layers. By computer calculations, we show how pattern formations, autowaves and classical waves can be regenerated in the networks, and describe the properties of these phenomena in detail. In particular, we focus our discussion on the necessary conditions for generating these spatio-temporal phenomena. In addition, the influences of the template parameters and initial state conditions of CNNs on the spatio-temporal phenomena are investigated.

In this paper, a novel Wold decomposition algorithm is proposed to address the issue of deterministic component extraction for texture images. This algorithm exploits the wavelet-based singularity detection theory to process both harmonic a nd evanescent features from frequency domain. This exploitation is based on the 2D Lebesgue decomposition theory. When applying multiresolution analysis techniq ue to the power spectrum density (PSD) of a regular homogeneous random field, its indeterministic component will be effectively smoothed, and its deterministic component will remain dominant at coarse scale. By means of propagating these positions to the finest scale, the deterministic component can be properly extracted. From experiment, the proposed algorithm can obtain results that satisfactorily ensure its robustness and efficiency.

The modeling of an application domain and its specific knowledge description language are important for developing knowledge-based systems. A rapid-prototyping approach is suitable for such developments since in this approach the modeling and language development are processed simultaneously. However, programming languages and their supporting environments which are usually used for prototyping are not necessarily adequate for developing practical applications. We have been developing an integrated development environment for knowledge-based systems, which supports all the development phases from the early prototyping phase to final commercial development phase. The environment called INSIDE is based on a Prolog abstract machine, and provides all of the functions required for the development of practical applications in addition to the standard Prolog features. This enables the development of both prototypes and practical applications in the same environment. Moreover, their efficient development and maintenance can be achieved. In addition, the effectiveness of INSIDE is described by examples of its practical application.