In this paper, efficient algorithms for content-based video retrieval using motion information are proposed. We describe algorithms for temporal scale invariant retrieval using Distance transformation and temporal scale absolute retrieval using Motion Retrieval Code. The effectiveness of the proposed algorithms has been verified by experimental results.

This paper proposes a new algorithm to achieve about two-times speedup of modular exponentiation which is implemented by Montgomery multiplication based on Residue Number Systems (RNS). In RNS Montgomery multiplication, its performance is determined by two base transformations dominantly. For the purpose of realizing parallel processing of these base transformations, i. e. "duplicate processing," we present two procedures of RNS Montgomery multiplication, in which RNS bases a and b are interchanged, and perform them alternately in modular exponentiation iteration. In an investigation of implementation, 1.87-times speedup has been obtained for 1024-bit modular multiplication. The proposed RNS Montgomery multiplication algorithm has an advantage in achieving the performance corresponding to that the upper limit of the number of parallel processing units is doubled.

A numerical model of thin-film transistors for circuit simulation has been developed. This model utilizes three schemes. First, the spline interpolation with transformation by y=x+log(x) achieves excellent preciseness for both on-current and off-current simultaneously. Second, the square polynomial supplement solves an anomaly near the points where drain voltage equal to zero. Third, the linear extrapolation achieves continuities of the current and its derivatives as a function of voltages out of the area where the spline interpolation is performed, and improves convergence during circuit simulation.

Deep submicron technology calls for new design techniques, in which wire and gate delays are accounted to have equal or nearly equal effect on circuit behavior. Asynchronous speed-independent (SI) circuits, whose behavior is only robust to gate delay variations, may be too optimistic. On the other hand, building circuits totally delay-insensitive (DI), for both gates and wires, is impractical because of the lack of effective synthesis methods. The paper presents a new approach for synthesis of globally DI and locally SI circuits. The method, working in two possible design scenarios, either starts from a behavioral specification called Signal Transition Graph (STG) or from the SI implementation of the STG specification. The method locally modifies the initial model in such a way that the resultant behavior of the system does not depend on delays in the input wires. This guarantees delay-insensitivity of the system-environment interface. The suggested approach was successfully tested on a set of benchmarks. Experimental results show that DI interfacing is realized with a relatively moderate cost in area and speed (costs about 40% area penalty and 20% speed penalty).

In this paper, we present a novel algorithm to the alternative wiring problem by analyzing the implication relationship between nodes of alternative wires. Alternative wiring, or rewiring, refers to the process of adding a redundant connection to a circuit so as to make a target connection redundant and removable from the circuit without altering the functionality of the circuit. The well-known ATPG-based alternative wiring scheme, Redundancy Addition and Removal for Multi-level Boolean Optimization (RAMBO), has shown its effectiveness in solving the problem in the last decade. But, the deficiency of RAMBO lies in its long execution time for redundancy identification among a large set of candidate alternative wires. Our approaches of redundancy identification by source node and destination node implication relationship indicate that a large subset of unnecessary redundancy check processes can be further avoided to improve the efficiency significantly. We propose an algorithm, the Implication Based Alternative Wiring Logic Transformation (IBAW), to integrate the two adroit techniques. IBAW provides a competent solution to the alternative wiring problem and shows an outstanding efficiency in our experiments. Experiments were performed on MCNC benchmark circuits. Results show that IBAW runs 6.8 times faster than the original RAMBO in locating alternative wires and solution quality is maintained.

In this paper, we focus on an image encryption scheme based on a truncated Baker transformation. The truncated Baker transformation globally preserves the original dynamics of Baker transformation but incorporates a random local rotation operator between two neighbor elements in the mapping domain in order to keep a finite precision. It generates binary sequences (the dynamics of elements) which have statistically good features on ergodicity, mixing and chaotic properties. The image encryption scheme extended from the truncated Baker transformation efficiently shuffles the input gray level image satisfying fundamental conditions on confusion and diffusion required for image encryption schemes. However, this scheme uses many binary sequences and thus needs to keep a large volume of secret keys. In order to solve this problem we introduce Peano space-filling curve in this scheme, which remarkably reduce the key size and mapping iterations without deteriorating good shuffling properties attained by this scheme.

The skeleton and the skeleton function of an object are important representations for shape analysis and recognition. They contain enough information to recognize an object and to reconstruct its original shape. However, they are sensitive to distortion caused by rotation and noise. This paper presents another approach for binary object representation called a modified exoskeleton(mES) that combines the previously defined exoskeleton with the use of symmetric object whose dominant property is rotation invariant. The mES is the skeleton of a circular background around the object that preserves the skeleton properties including significant information about the object for use in object recognition. Then the matching algorithm for object recognition based on the mES is presented. We applied the matching algorithm to evaluate the mES against the skeleton obtained from using 4-neighbor distance transformation on a set of artificial objects, and the experimental results reveal that the mES is more robust to distortion caused by rotation and noise than the skeleton and that the matching algorithm is capable of recognizing objects effectively regardless of their size and orientation.

The constant-Q based wavelet transform is the most effective means of quantitatively characterizing high frequency transient signals. This study develops a novel non constant-Q based multi-resolution transform (NCQM) and provides a precision analysis descriptor for both low and high frequency transients. The properties of this novel NCQM kernel are thoroughly examined and then the striking conceptual resemblance, energy conservation characteristic, and power spectrum close forms are derived. The rapid algorithm of NCQM is also presented and its excellent performance in noisy environments is demonstrated.

In screening for primary lung cancer with plain chest radiography, computer-aided diagnosis systems are being developed to reduce chest radiologists' task and the risk of missing positive cases. We evaluated a difference filter that enhances nodule densities in the preprocessing of chest X-ray images. Since ribs often affect detection of pulmonary nodules, we designed an eye-shaped filter to fit the rib shape. Although this filter increased the nodule detection rate, it could not detect nodules near the thoracic wall. The thoracic wall was then outlined by computers with Hough transformation for line detection. On the basis of the outline, the direction of the eye-shaped filter was determined. With this technique, the filter was not affected by considerable changes in the shape of anatomical structures, such as ribs and the thoracic wall, and could detect pulmonary nodules regardless of their location.

This paper first gives the exact surface integral representation for PO diffracted electromagnetic fields from bounded flat plate through the deformations of the original surface by using field equivalence principle. This exact representation with the surface integral can be approximately reduced to novel line integral along the boundary of the plate by the use of Maggi-Rubinowicz transformation, which keeps a high accuracy even in near zone. Numerical results for the scattering of the electric dipole wave from the square planar plate are presented for demonstrating the accuracy.

This paper presents a new effective partitioning technique of linearly transformed input space in Adaptive Network based Fuzzy Inference System (ANFIS). The ANFIS is the fuzzy system with a hybrid parameter learning method, which is composed of a gradient and a least square method. The input space can be partitioned flexibly using new modeling inputs, which are the weighted linear combination of the original inputs by the proposed input partitioning technique, thus, the parameter learning time and the modeling error of ANFIS can be reduced. The simulation result illustrates the effectiveness of the proposed technique.

In this paper, the effective uses of Gerschgorin radii of the similar transformed covariance matrix for source number estimation are introduced. A heuristic approach is used for developing the detection criteria. The heuristic approach applying the visual Gerschgorin disk method (VGD), developed from the projection concept, overcomes the problems in cases of small data samples, an unknown noise model, and data dependency. Furthermore, Gerschgorin disks can be formed into two distinct, non-overlapping collections; one for signals and the other for noises. The number of sources can be visually determined by counting the number of Gerschgorin disks for signals. The proposed method is based on the sample correlation coefficient to normalize the signal Gerschgorin radii for source number detection. The performance of VGD shows improved detection capabilities over Gerschgorin Disk Estimator (GDE) in Gaussian white noise process and was used successfully in measured experimental data.

We propose a novel Bragg grating filter synthesis method using a Fourier transform of the target scattering matrix. Multiple scattering processes are taken into account by iteration to improve the synthesis accuracy.

In this paper, a new frequency transformation for complex analog filter design which is suitable for integration is discussed. Arbitrary specified passband and stopband edges are easily transformed into those of the normalized LPF by solving simultaneous equations with four unknowns. Different from previous methods, the proposed transformation provides better performance in active realization of complex filters.

A new digital watermark approach based on fractal image coding is proposed in this letter. We present a way to use the fractal code as a means of embedding a watermark. The proposed approach has shown to be resistant to the JPEG lossy compression. Moreover, the digital watermark can be simply extracted from the watermarked image without resorting to the original image.

This paper describes a scheme to capture a wide-view image using a camera setup with uncalibrated cameras. The setup is such that the optical axes are pointed in divergent directions. The direction of view of the resulting image can be chosen freely in any direction between these two optical axes. The scheme uses eight-parameter perspective transformations to warp the images, the parameters of which are obtained by using a relative orientation algorithm. The focal length and scale factor of the two images are estimated by using Powell's multi-dimensional optimization technique. Experiments on real images show the accuracy of the scheme.

A large number of techniques have been proposed for acceleration of the Hough Transform, because the transformation is computationally very expensive in general. It is known that the sampling interval in parameter space is strongly related to the computation cost. The precision of the transformation and the processing speed are in a trade-off relationship. No fair comparison of the processing speed between various methods was performed in all previous works, because no criterion had been given for the sampling interval of parameter, and because the precision of parameter was not equal between methods. At the beginning of our research, we derive the relationship between the sampling interval and the precision of parameter. Then we derive a framework for comparing computation cost under equal condition for precision of parameter, regarding the total number of sampling points of a parameter as the computation cost. We define the transformation error in the Hough Transform, and the error is regarded as transformation noise. In this paper we also propose a design method called "Noise-level Shaping," by which we can set the transformation noise to an arbitrarily level. The level of the noise is varied according to the value of a parameter. Noise-level Shaping makes it possible for us to find the efficient parameterization and to find the efficient sampling interval in a specific application of the Hough Transform.

As many research works are based on some previous results, my paper, namely The Integrated Scheduling and Allocation of High-Level Test Synthesis, makes use of some techniques by T. Kim. However, I did not state explicitly that some parts of my work are based on Kim's approach although I have referred to his paper. I would like to express my deep apology to Kim for not having emphasized Kim's contribution to my work. But my intention was not to steal Kim's ideas. I would like to emphasize the following difference.

I would like to draw the attention of the editorial board of IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences and its readers to a recent paper, Tianruo Yang, "The integrated scheduling and allocation of high-level test synthesis," vol. E82-A, no. 1, January 1999, pp. 145-158. (Here we call this paper the Yang's paper. ) Yang did not give the correct information about the originality of the paper. I will point out that the writings (and the idea accordingly) of section 6 of Yang's paper came from papers [1] and [2].

A method to recognize planar objects undergoing affine transformation is proposed in this paper. The method is based upon wavelet multiscale features and Hopfield neural networks. The feature vector consists of the multiscale wavelet transformed extremal evolution. The evolution contains the information of the contour primitives in a multiscale manner, which can be used to discriminate dominant points, hence a good initial state of the Hopfield network can be obtained. Such good initiation enables the network to converge more efficiently. A wavelet normalization scheme was applied to make our method scale invariant and to reduce the distortion resulting from normalizing the object contours. The Hopfield neural network was employed as a global processing mechanism for feature matching and made our method suitable to recognize planar objects whose shape distortion arising from an affine transformation. The Hopfield network was improved to guarantee unique and more stable matching results. A new matching evaluation scheme, which is computationally efficient, was proposed to evaluate the goodness of matching. Two sets of images, noiseless and noisy industrial tools, undergoing affine transformation were used to test the performance of the proposed method. Experimental results showed that our method is not only effective and robust under affine transformation but also can limit the effect of noises.