We have developed a neutron imaging system based on the penumbral imaging technique. The system consists of a penumbral aperture and a sensitive neutron detector. The aperture was made from a thick (6 cm) tungsten block with a toroidal taper. It can effectively block 14-MeV neutrons and provide a satisfactory sharp, isoplanatic (space-invariant) point spread function (PSF). A two-dimensional scintillator array, which is coupled with a gated two-stage image intensifier system and a CCD camera, was used as a sensitive neutron detector. It can record the neutron image with high sensitivity and high signal-to-noise ratio. The reconstruction was performed with a Wiener filter. The spatial resolution of the reconstructed neutron image was estimated to be 31 µm by computer simulation. Experimental demonstration has been achieved by imaging 14-MeV deuterium-tritium neutrons emitted from a laser-imploded target.

In this paper, we present a vision system for a depalletizing robot which recognizes carton objects. The algorithm consists of the extraction of object candidates and a labeling process to determine whether or not they actually exist. We consider this labeling a combinatorial optimization of labels, we propose a new labeling method applying Genetic Algorithm (GA). GA is an effective optimization method, but it has been inapplicable to real industrial systems because of its processing time and difficulty of finding the global optimum solution. We have solved these problems by using the following guidelines for designing GA: (1) encoding high-level information to chromosomes, such as the existence of object candidates; (2) proposing effective coding method and genetic operations based on the building block hypothesis; and (3) preparing a support procedure in the vision system for compensating for the mis-recognition caused by the pseudo optimum solution in labeling. Here, the hypothesis says that a better solution can be generated by combining parts of good solutions. In our problem, it is expected that a global desirable image interpretation can be obtained by combining subimages interpreted consistently. Through real image experiments, we have proven that the reliability of the vision system we have proposed is more than 98% and the recognition speed is 5 seconds/image, which is practical enough for the real-time robot task.

This paper proposes a robust method for detecting step and ramp edges. In this method, an edge is defined not as a point where there is a large change in intensity, but as a region boundary based on the separability of image features which can be calculated by linear discriminant analysis. Based on this definition of an edge, its intensity can be obtained from the separability, which depends only on the shape of an edge. This characteristic enables easy selection of the optimum threshold value for the extraction of an edge, and this method can be applied to color and texture edge extraction. Experimental results have demonstrated that this proposed method is robust to noise and dulled edges, and, in addition, allows easy selection of the optimum threshold value.

In order to evaluate quantitatively TMJ sound, TMJ sound in normal subject group, CMD patient group A with palpable sounds unknown to them, CMD patient group B with palpable sounds known to them, and CMD patient group C with audible sounds were detected by a contact microphone, and frequency analysis of the power spectra was performed. The power spectra of TMJ sound of normal subject group and patient group A showed patterns with frequency values below 100 Hz, whereas the power spectra of patient groups B and C showed distinctively different patterns with peaks of frequency component exceeding 100 Hz. As regards the cumulative frequency value, the patterns for each group clearly differed from those of other groups; in particular the 80% cumulative frequency value showed the greatest difference. From these results, it is assumed that the 80% cumulative frequency value can be used as an effective indicator for quantitative evaluation of TMJ sound.

In this paper we propose a new method for removing the characteristic of the piezoelectric transducer from the received signal in the pulse-echo method so that the time resolution in the determination of transit time of ultrasound in a thin layer is increased. The total characteristic of the pulse-echo system is described by cascade of distributed-constant systems for the ultrasonic transducer, matching layer, and acoustic medium. The input impedance is estimated by the inverse matrix of the cascade system and the voltage signal at the electrical port. From the inverse Fourier transform of input impedance, the transit time in a thin layer object is accurately determined with high time resolution. The principle of the method is confirmed by simulation experiments.

This paper presents a new internal image representation, in which the scene is encoded into a three-intensity-level image. This representation is generated by Laplacian-Gaussian filtering followed by dual-thresholding. We refer to this imege as three-level broad-edge representation. It supresses the high frequency noise and shading in the image and encodes the sign of relative intensity of a pixel compared with surrounding region. Image model search based on cross correlation using this representation is as reliable as the one based on gray normalized correlation, while it reduces the computational cost by 50 times. We examined the reliability and realtime performance of this method when it is applied to an industrial object recognition task. Our prototype system achieves 3232 image model search from the 128128 pixel area in 2 milli-seconds with a 9 MHz pixel clock image processor. This speed is fast enough for searching and tracking a single object at video frame rate.

A new method is proposed for realizing a flexible change detection which is free from the limitation that multitemporal images must have the same spectral bands whose center wavelength and bandwidth are identical. As spaceborne multispectral scanners are continuously improved for performance and new scanners do not necessarily have the same spaectral bands for observation, this limitation is a serious obstacle for detecting long term temporal change. The proposed method removes this limitation by using an image normalization technique based on multiple regression analysis. The method is successfully applied to actual remotely sensed multitemporal images.

There have been many developments on neural network research, and ability of a multi-layered network for classification of multi-spectral image data has been studied. We can classify non-Gaussian distributed data using the neural network trained by a back-propagation method (BPM) because it is independent of noise conditions. The BPM is a supervised classifier, so that we can get a high classification accuracy by using the method, so long as we can choose the good training data set. However, the multi-spectral data have many kinds of category information in a pixel because of its pixel resolution of the sensor. The data should be separated in many clusters even if they belong to a same class. Therefore, it is difficult to choose the good training data set which extract the characteristics of the class. Up to now, the researchers have chosen the training data set by random sampling from the input data. To overcome the problem, a hybrid pattern classification system using BPM and Kohonens feature mapping (KFM) has been proposed recently. The system performed choosing the training data set from the result of rough classification using KFM. However, how the remotely sensed data had been influenced by the KFM has not been demonstrated quantitatively. In this paper, we propose a new approach using the competitive weight vectors as the training data set, because we consider that a competitive unit represents a small cluster of the input patterns. The approach makes the training data set choice work easier than the usual one, because the KFM can automatically self-organize a topological relation among the target image patterns on a competitive plane. We demonstrate that the representative of the competitive units by principal component analysis (PCA). We also illustrate that the approach improves the classification accuracy by applying it on the classification of the real remotely sensed data.

This paper investigates the problems which inhibits the use of today's WDM networks. These are propagation delay, packet processing overhead, bit & frame synchronization, and tuning latency. So far, these problems, especially propagation delay, have been ignored in most performance analysis papers. They have always hindered network designers, but they are magnified by the order of magnitude increase in speed of optical communications systems as compared to previous media. This paper examines the impact of the propagation delay on the performance of WDM protocols with variations in the number of channels, packet length and system size, specifically in two reservation based protocols with control channels and two pre-allocation protocols without the control channels. Also the impact of three delay factors (packet processing overhead, bit & frame synchronization and tuning latency) are studied with different propagation delay parameters. In reservation protocols, each node has one agile transmitter and two receivers; one of them is fixed and the other one is agile. The fixed receiver continuously monitors the control channel, receives all control packets, and updates their own status tables in order to track the availability of the other nodes as a target and data channels to avoid the destination collisions and the data channel collisions, respectively. In pre-allocation protocols, each node has a tunable transmitter, a fixed or slow tunable receiver, and its own home channel to receive the packets. The performance of this protocol is evaluated through the discrete-event simulation in terms of the average packet delay and network throughput.

Based on a simple model for the statistical error characteristics of range sensing, a numerical scheme called renormalization is presented for optimally fitting a planar surface to data points obtained by range sensing. The renormalization method has the advantage that not only an optimal fit is computed but also its reliability is automatically evaluated in the form of the covariance matrix. Its effectiveness is demonstrated by numerical simulation. A scheme for visualizing the reliability of computation by means of the primary deviation pair is also presented.

We have developed a design technique for static logic circuits. Using this technique, we designed 1/2 divider-type 1:4 demultiplexer (DEMUX) and 2:1 selector-type 4:1 multiplexer (MUX) circuits, each of which is a key component in high-speed data multiplexing and demultiplexing. These circuits consist of double rail flip-flops (DR F/F). These flip-flops have a smaller mean internal capacitance than single rail flip-flops, making them suitable for high-speed operation. The DR F/F has a symmetric structure, so the double rail toggle flip-flop can put out an exactly balanced CK/CKN signal, which boosts the speed of the data flip-flops. The double rail structure enables 30% faster operation but consumes only 17% more power (per GHz) than a single rail circuit. In addition, our 0.25-µm process technology provides a 70% higher frequency operation than 0.5-µm process technology. At the supply voltage of 2.2 V, the DEMUX circuit and the MUX circuit operate at 4.55 GHz and 2.98 GHz, respectively. In addition, the 0.25-µm DEMUX circuit and the MUX circuit respectively consume 6.0 mW/GHz and 13.7 mW/GHz (＠1.3 V), which are only 12% of the power consumed by 3.3-V 0.5-µm circuits. Because of its high-speed and low-power characteristics, our design technique will greatly contribute to the progress of large-scale high-speed telecommunication systems.

A new high performance digital signal processor (DSP) that lowers power consumption, reduces chip count, and enables system cost savings for wireless communications applications was developed. The new device contains high performance, hard-wired functionality with a specialized instruction set to effectively implement the worldwide digital cellular standard algorithms, including GSM, PDC and NADC, and also features both full rate and future half rate processing by software modules. The device provides a wider operating voltage ranging from 1.5 V to 5.5 V using 5 V process based on the market requirement of 5 V supply voltage, even though a power supply voltage in most applications will be shifted to 3 V. Several circuits was newly developed to achieve low power consumption and high speed operation at both 5 V and 3 V process using the same data base. The device also features over 50 MIPS of processing power with low power consumption and 100 nA stand-by current at either 3 V or 5 V. One remarkable advantage is a flexible CPU core approach for the future spin-off devices with different ROM/RAM configurations and peripheral modules without requiring any CPU design changes. This paper describes the architecture of a lower power and high speed design with effective hardware and software modules implementations.

The Bidirectional Reflectance Distribution Function (BRDF) is an intrinsic measurement of directional properties of the earth's surface. However, the estimation of the BRDF requires many remote sensing measurements of a given surface target from different viewing angles. In addition, a good atmospheric correction scheme is a prerequisite for such an attempt. The airborne POLDER sensor measures successively reflected radiation by terrestrial surfaces in a framed image form at different viewing angles during a single airplane pass, like taking snap-shot pictures. A specially improved atmospheric correction algorithm which is applicable to a framed image data by POLDER sensor is presented. The observed reflectance images taken successively by the airborne POLDER at slightly different viewing angles are converted to a series of surface albedo images by applying our atmospheric correction algorithm. Then, the BRDFs for three surface covers, namely, "River Water," "Forest," and "Rice Field," are estimated by using successive albedo images. It is found that the BRDF for "River Water" follows Lambert law at both 550nm and 850nm. It is also found that the BRDFs for "Forest" and "Rice Field" follow Lambert's law at 550nm, but they follow an anisotropic reflection law at 850nm and fitting parameters for their BRDFs are presented.

A non-invasive method is proposed to estimate the location of intracranial vascular disease using several sensors placed on the forehead. The advantage of this method over earlier measurements with a single ocular sensor is the abilty to localize the region of abnormal vascular tissue. A weighted least mean square procedure is applied to estimating the time difference between the sensor outputs using the phase distribution in the cross-spectrum. It is possible to estimate time differences shorter than sampling period. Computer simulation and clinical experiments demonstrate that a distance difference of around 20 times shorter than the wavelength can be obtained.

This paper describes ALINX (Advanced Low-voltage Interface Circuit System), a low-power and high-speed interface circuit of submicron CMOS LSI for digital information and telecommunications systems. Differential and single-ended ALINXs are low-voltage swing I/O interface circuits with less than 1.0 V swing from a 1.2 V supply. Specifically, the differential ALINX features a pair of complementary NMOS push-pull drivers operating from a 1.2 V supply, reducing power consumption compared to conventional high-speed interface circuits operating from a 5 V or 3.3 V supply. The DC power consumption is approximately 11% of ECL. We observed 622 Mbps differential transmission with 8 mW power consumption and single-ended transmission at 311 Mbps with 14 mW with a PN23 pseudo-random pattern. We also describe a noise characteristic and ALINX applications to high-speed data buses and LSI for telecommunications systems. A time/space switch LSI with 0.9 W total power consumption was fabricated by 0.5 µm CMOS process technology. This chip can use a plastic QFP.

In VLSI or PCB layout, one often encounters a region that is either of rectilinear shape or can be approximated by a rectilinear region. Although many placement methods have been proposed, most of them are applicable only to rectangular regions. For these algorithms to be applied to a rectilinear region, two processing steps, region partitioning and rectangular region cell placement are necessary. Hence, the placement results are so far dependent on the locations of the regions partitioned and frequently become trapped in local minima. Recently, neural networks have been suggested as a new way to resolve the cell placement problem. This paper proposed a unified modeling method that uses a neural net model with additional calibration nodes to model rectilinear region cell placement. In this method, the ideal distance between cells is preserved to simultaneously minimize both the total wire length and the module overlap. Unlike traditional approaches, the proposed algorithm requires only a single processing step. Experiments have been conducted to verify the performance of the proposed algorithm. The total wire length obtained by our method is shorter than those generated by previous methods.

Petri nets are useful in modeling and analyzing various types of discrete-event systems such as parallel processing systems, distributed systems, and sequential control systems, because Petri nets can easily be used to represent such properties of these systems as concurrency, nondecidability, and causality. Various behavioral analytic problems on Petri nets are reduced to reachability and liveness on them. It is also known that the decidability of liveness is equivalent to that of reachability which is solvable. However, useful necessary and sufficient structural liveness conditions have been given only for extended free-choice (EFC) nets and their subclasses. Moreover recently, a necessary and sufficient structural liveness condition for a useful subclass NKT=(SKT, TKT, FKT, MoKT) (i.e., a Petri net in which each minimal structural deadlock (MSDL) contains at least one real or virtual kindling trap, each locally structural-live MSDL ND=(SD, TD, FD, MoD) is never globally dead even if all key transitions for local liveness of each MSDL are controlled by the net of SKTSD s.t. SKTSD, and there exists no singular MSDL of type (α)) has also been given. In this paper, in order to give one of the bases for a necessary and sufficient "structural" or "initial-marking-based" liveness condition for a general Petri net N, we will, first, directly present a necessary and sufficient local liveness condition for each MSDL with a real deadlock-trap structure in a subclass Ñ (N) using the net structure and initial token distribution and extending basic concepts used in NKT, where Ñ is a general Petri net without live behavioral traps, local liveness means a useful necessary condition for the above final goal, and real deadlock-trap structure means that each MSDL in Ñ contains at least one minimal structural trap. Secondly, a new subclass is shown in which, if the above locally structural liveness condition for each MSDL holds, then the whole-net liveness is also guaranteed. It is also argued that the obtained results are applicable to describing new live behavioral traps and deriving a necessary and sufficient structural liveness condition, which is the final goal in this work, for a general Petri net N.

This paper presents some tighter bounds on universal noiseless coding, in particular, the lowerbound tighter than Davisson et al.'s for finite sequence and the upperbound for some typical universal data compression. We find that Davisson et al.'s bound satisfies some optimization in the case of using the Jeffreys prior and also that the derived upperbound in this paper is within O(1/n) from the Clarke and Barron asymptotics in the case of some restricted typical universal data compression defined in the paper.

This paper presents a new method for solving the structure-from-motion problem for optical flow. The fact that the structure-from-motion problem can be simplified by using the linearization technique is well known. However, it has been pointed out that the linearization technique reduces the accuracy of the computation. In this paper, we overcome this disadvantage by correcting the linearized solution in a statistically optimal way. Computer simulation experiments show that our method yields an unbiased estimator of the motion parameters which almost attains the theoretical bound on accuracy. Our method also enables us to evaluate the reliability of the reconstructed structure in the form of the covariance matrix. Real-image experiments are conducted to demonstrate the effectiveness of our method.

This paper proposes a new method that can robustly recover 3D structure and 3D motion of 3D moving objects from a few multi-views. It recovers 3D feature points by obtaining intersections of back-projection lines which are connected from the camera's optical centers thorough projected feature points on the image planes corresponding to the different cameras. We show that our method needs only six views to suppress false 3D feature points in most cases by discussing the relation between the occurrence probability of false 3D feature points and the number of views. This discussion gives us a criterion to design the optimal multi-camera system for recovering 3D structure and 3D motion of 3D moving objects. An experimental multi-camera system is constructed to confirm the validity of our method. This system can take images from six different views at once and record motion image sequence from each view over a period of a few seconds. It is tested successfully on recovering the 3D structure of Vinus's plaster head and on recovering the 3D structure and 3D motion of a moving hand.