We propose a motion estimation algorithm using less gray level images, which are composed of bits pixels lower than 8 bits pixels. Threshold values for generating low bits pixels from 8 bits pixels are simply determined as median values of pixels in a macro block. The proposed algorithm reduces the computational complexity of motion estimation at less expense of video quality. Moreover, median cut quantization can be applied to multilevel images and combined with a lot of fast algorithms to obtain more effective algorithms.

In this paper, we propose an adaptive predictive coding method based on image segmentation for lossless compression. MAR (Multiplicative Autoregressive) predictive coding is an efficient lossless compression scheme. Predictors of the MAR model can be adapted to changes in the local image statistics due to its local image processing. However, the performance of the MAR method is reduced when applied to images whose local statistics change within the block-by-block subdivided image. Furthermore, side-information such as prediction coefficients must be transmitted to the decoder with each block. In order to enhance the compression performance, we improve the MAR coding method by using image segmentation. The proposed MAR predictor can be adapted to the local statistics of the image efficiently at each pixel. Furthermore, less side-information need be transmitted compared with the conventional MAR method.

Congestion Control Scheme of TCP/IP protocol suite is established by Transmission Control Protocol (TCP). Using the self-clocking scheme, TCP is able to maintain a quick optimum connection status for the network path, unless it is given an excessive load to carry to the network. However, in wide area networks, there are some obstructive factors for the self-clocking scheme of TCP. In this paper, we describe the obstructive factors for the self-clocking scheme. We propose a new congestion control scheme using a packet pair scheme and a traffic-shaping scheme. In combining these schemes with TCP, new TCP options and a modification for TCP congestion control algorithms are added. Using our scheme, TCP is able to maintain smooth self-clocking. We implemented this scheme on a network simulator for evaluation. Compared with normal TCP, this scheme was demonstrated to be over 20% more efficient in symmetric communication and over 40% more efficient in asymmetric communication.

Human faces convey various information, including that is specific to each individual person and that is part of mutual communication among persons. Information exhibited by a "face" is what is called "non-verbal information" and usually verbal media cannot easily describe such information appropriately. Recently, detailed studies on the processing of face images by a computer have been carried out in the engineering field for applications to communication media and human computer interaction as well as automatic identification of human faces. Two main technical topics are the recognition of human faces and the synthesis of face images. The objective of the former is to enable a computer to detect and identify users and further to recognize their facial expressions, while that of the latter is to provide a natural and impressive user interface on a computer in the form of a "face. " These studies have also been found to be useful in various non-engineering fields related to a face, such as psychology, anthropology, cosmetology and dentistry. Most of the studies in these different fields have been carried out independently up to now, although all of them deal with a "face. " Now in virtue of the progress in the above engineering technologies a common study tools and databases for facial information have become available. On the basis of these backgrounds, this paper surveys recent research trends in the processing of face images by a computer and its typical applications. Firstly, the various characteristics of faces are considered. Secondly, recent research activities in the recognition and synthesis of face images are outlined. Thirdly, the applications of digital processing methods of facial information are discussed from several standpoints: intelligent image coding, media handling, human computer interaction, caricature, facial impression, psychological and medical applications. The common tools and databases used in the studies of processing of facial information and some related topics are also described.

This paper surveys the results of various studies on 3-D image coding. Themes are focused on efficient compression and display-independent representation of 3-D images. Most of the works on 3-D image coding have been concentrated on the compression methods tuned for each of the 3-D image formats (stereo pairs, multi-view images, volumetric images, holograms and so on). For the compression of stereo images, several techniques concerned with the concept of disparity compensation have been developed. For the compression of multi-view images, the concepts of disparity compensation and epipolar plane image (EPI) are the efficient ways of exploiting redundancies between multiple views. These techniques, however, heavily depend on the limited camera configurations. In order to consider many other multi-view configurations and other types of 3-D images comprehensively, more general platform for the 3-D image representation is introduced, aiming to outgrow the framework of 3-D "image" communication and to open up a novel field of technology, which should be called the "spatial" communication. Especially, the light ray based method has a wide range of application, including efficient transmission of the physical world, as well as integration of the virtual and physical worlds.

In this paper, a scheme to remove clouds and their shadows from remotely sensed images of Landsat TM over land has been proposed. The scheme uses the image fusion technique to automatically recognize and remove contamination of clouds and their shadows, and integrate complementary information into the composite image from multitemporal images. The cloud regions can be detected on the basis of the reflectance differences with the other regions. Based on the fact that shadows smooth the brightness changes of the ground, the shadow regions can be detected successfully by means of wavelet transform. Further, an area-based detection rule is developed in this paper and the multispectral characteristics of Landsat TM images are used to alleviate the computational load. Because the wavelet transform is adopted for the image fusion, artifacts are invisible in the fused images. Finally, the performance of the proposed scheme is demonstrated experimentally.

Much of the data we deal with every day is organized hierarchically: file systems, library classification schemes and yellow page categories are salient examples. Business data too, benefits from a hierarchical organization, and indeed the hierarchical data model was quite prevalent thirty years ago. Due to the recently increased importance of X. 500/LDAP directories, which are hierarchical, and the prevalence of aggregation hierarchies in datacubes, there is now renewed interest in the hierarchical organization of data. In this paper, we develop a framework for a modern hierarchical data model, substantially improved from the original version by taking advantage of the lessons learned in the relational database context. We argue that this new hierarchical data model has many benefits with respect to the ubiquitous flat relational data model.

The Available Bit Rate (ABR) service of Asynchronous Transfer Mode (ATM) networks employs explicit rate notification algorithms to ensure better and fair distribution of available bandwidth among contending sources. The Enhanced Proportional Rate Control Algorithm (EPRCA) is one of the explicit rate control algorithms recommended by the ATM forum. In this paper, we identify deficiencies and problems associated with EPRCA and show that these cause unfairness in bandwidth utilization by the contending sources. We propose modification in EPRCA and call it Modified Enhanced Proportional Rate Control Algorithm (EPRCAM). We will argue and show through simulation results that EPRCAM leads to better link utilization and fair bandwidth allocation among contending sources. In our simulation model, EPRCAM results in as high as 97. 8% link utilization without cell loss.

In order to improve fairness and stability of TCP best-effort service we propose a new congestion control algorithm using packet loss information obtained from Selective Acknowledgments (SACK), and evaluate its effectiveness by simulation. The proposed scheme is for an environment consisting of Random Early Detection (RED) routers which drop each arriving packet with a certain probability after a threshold. The proposed mechanism adjusts the decrease in congestion window for Fast Recovery and the increase in congestion window per ACK during the congestion avoidance phase according to the number of lost packets. Simulation results show that not only the bandwidth allocation fairness is improved but also throughput deviation is markedly reduced resulting in more stable transport capability.

A GeSi avalanche photodetector grown on a silicon-on-insulator (SOI) passive waveguide is demonstrated. The absorption layer of the detector consisits of alternating layers of 66 Ge0. 44Si0. 56 and 480 Si on SOI substrate. The thick SOI waveguide couples the light from an optical fiber into the GeSi/Si strain-limited thin absorption region. The detector exhibits low dark current, sharp breakdown and an external responsivity of 0. 2 A/W at 1. 3 µm wavelength.

It is urgently required to protect copyrights of digital contents since the digital contents can be easily copied without degradation of quality. In this paper, we propose a new watermarking method which spreads an ID pattern with a random sequence and embeds it throughout the spatial domain of a color image. The random sequence is a key for extracting the ID pattern. As an ID pattern is spread throughout an image, we can extract the ID pattern from a part of the image, that is clipped image. We can also confirm authenticity by extracting the same ID pattern from several parts of an image. The proposed method is robust to disturbance by noise addition and image conversion such as brightness-contrast conversion and JPEG compression.

We propose an information integration architecture for a man-machine interface to construct a new agent-based Computer Supported Cooperative Work (CSCW) system. The system acts as a clerk in cooperative work giving users the advantage of using cooperative work space. The system allows users to do their work in the style of an ordinary meeting because spontaneous expressions of speech and gestures by users are detected by sensors so that they can be integrated with a task model at several levels to create suitable responses in a man-machine interface. As a result, users can dedicate themselves to mutually understand other meeting members with no awareness of direction to the CSCW system. In this paper, we describe the whole system and its information integration architecture for the man-machine interface including, the principle of functions, the current status of the system and future directions.

In our current work, we attempt to make an automatic diagnostic system of lung cancer based on the analysis of the sputum color images. In order to form general diagnostic rules, we have collected a database with thousands of sputum color images from normal and abnormal subjects. As a first step, in this paper, we present a segmentation method of sputum color images prepared by the Papanicalaou standard staining method. The segmentation is performed based on an energy function minimization using an unsupervised Hopfield neural network (HNN). This HNN have been used for the segmentation of magnetic resonance images (MRI). The results have been acceptable, however the method have some limitations due to the stuck of the network in an early local minimum because the energy landscape in general has more than one local minimum due to the nonconvex nature of the energy surface. To overcome this problem, we have suggested in our previous work some contributions. Similarly to the MRI images, the color images can be considered as multidimensional data as each pixel is represented by its three components in the RGB image planes. To the input of HNN we have applied the RGB components of several sputum images. However, the extreme variations in the gray-levels of the images and the relative contrast among nuclei due to unavoidable staining variations among individual cells, the cytoplasm folds and the debris cells, make the segmentation less accurate and impossible its automatization as the number of regions is difficult to be estimated in advance. On the other hand, the most important objective in processing cell clusters is the detection and accurate segmentation of the nuclei, because most quantitative procedures are based on measurements of nuclear features. For this reason, based on our collected database of sputum color images, we found an algorithm for NonSputum cell masking. Once these masked images are determined, they are given, with some of the RGB components of the raw image, to the input of HNN to make a crisp segmentation by assigning each pixel to label such as Background, Cytoplasm, and Nucleus. The proposed technique has yielded correct segmentation of complex scene of sputum prepared by ordinary manual staining method in most of the tested images selected from our database containing thousands of sputum color images.

We propose a Generalized Order Statistic Cell Averaging (GOSCA) CFAR detector. The weighted sums of the order statistics in the leading and lagging reference windows are utilized for the background level estimate. The estimate is obtained by averaging the weighted sums. By changing the weighting values, various CFAR detectors are obtained. The main advantage of the proposed GOSCA CFAR detector over the GOS CFAR detector is to reduce a computational time which is critical factor for the real time operation. We also derive unified formulas of the GOSCA CFAR detector under the noncoherent integration scheme. For Swerling target cases, performances of various CFAR detectors implemented using the GOSCA CFAR detector are derived and compared in homogeneous environment, and in the case of multiple targets and clutter edges situations.

This paper shows new techniques to construct a service network which realizes responsive large-size data transmission for widely distributed mass users. We set our service target as transferring mega-byte scale data from a server to a client within one second. ATM is recognized as a powerful technology with which to construct a wide area network infrastructure that supports multiple bandwidth services. Our fundamental principles in developing such a service network are as follows: a) The bandwidth sharing mechanism should be of the best effort rather than resource reservation type. This is because only best effort schemes remove bandwidth reservation/release overheads. b) More than a 100 Mb/s data transmission rate should be supported throughout data transfer. c) Data transfer should be completed within the round trip through the network (or a small multiple thereof). This is necessary to minimize the effect of transmission time in large-scale networks. d) The user network interface should be simply defined to allow independent evolution of both network and terminal technologies. e) Congestion control must block the spread of congestion within the network. Based on these principles, we propose the "ATM superpacket network (ATM-SN)" as the service network to realize our target service. Key techniques are as follows. (1) Best effort and cut-through transmission of superpackets whose length reaches ten mega-bytes. (2) Network nodes with large-capacity buffer memories that prevent superpacket collisions. (3) Superpacket admission control at network nodes to prevent cell overflow. (4) Superpacket-based congestion control. Our proposal assumes the existence of a high-quality ATM infrastructure that can provide a large bandwidth with a high-quality DBR cell transmission capability (cell loss ratio is less than 10E-7) and small bit error ratios (less than 10E-10). First, we detail our proposal of the ATM-SN. Next, we propose a superpacket-based congestion control technique coupled with a simple Usage Parameter Control function. We then show the evaluation results of those key techniques to confirm the effectiveness of the superpacket network.

One of the important challenges in the design of ATM networks is how to provide quality-of-service (QoS) while maintaining high network resource utilization. In this paper, we discuss the role of real-time traffic characterization in QoS control for ATM networks and review several approaches to the problem of resource allocation. We then describe a particular framework for QoS control in which real-time measurements of a connection stream are used to determine appropriate parameters for usage parameter control (UPC). Connection admission control (CAC) is based on the characterization of the aggregate stream in terms of the individual stream UPC descriptors, together with real-time measurements.

The classical max-min policy has been suggested by the ATM Forum to support the available bit rate (ABR) service class. However, there are several drawbacks in adopting the max-min rate allocation policy. In particular, the max-min policy is not able to support the minimum cell rate (MCR) requirement and the peak cell rate (PCR) constraint for each ABR connection. Furthermore, the max-min policy does not offer flexible options for network providers wishing to establish a usage-based pricing criterion. In this paper, we present a generic weight-based rate allocation policy, which generalizes the classical max-min policy by supporting the MCR/PCR for each connection. Our rate allocation policy offers a flexible usage-based pricing strategy to network providers. A centralized algorithm is presented to compute network-wide bandwidth allocation to achieve this policy. Furthermore, a simple switch algorithm using ABR flow control protocol is developed with the aim of achieving our rate allocation policy in a distributed networking environment. The effectiveness of our distributed algorithm in a local area environment is substantiated by simulation results based on the benchmark network configurations suggested by the ATM Forum.

Many Ziv-Lempel algorithms have a similar property, that is, slow encoding and fast decoding. This paper proposes a simple improved Ziv-Lempel algorithm to encode a large amount of data quickly as well as compactly by using multiple-processor system.

We introduce a subclass of context-free languages, called pure context-free (PCF) languages, which is generated by context-free grammars with only one type of symbol (i. e. , terminals and nonterminals are not distinguished), and consider the problem of identifying paralleled even monogenic pure context-free (pem-PCF) languages, PCF languages with restricted and enhanced features, from positive data only. In this paper we show that the ploblem of identifying the class of pem-PCF languages is reduced to the ploblem of identifying the class of monogenic PCF (mono-PCF), by decomposing each string of pem-PCF languages. Then, with its result, we show that the class of pem-PCF languages is polynomial time identifiable in the limit from positive data. Further, we refer to properties of its identification algorithm.

This paper studies a congestion control scheme in integrated variable bit-rate video, audio and data (e. g. , image or text) communications, where each video stream is synchronized with the corresponding audio stream. When the audio and video streams are output, media synchronization control is performed. To avoid congestion, we employ a dynamic video resolution control scheme which dynamically changes the video encoding rate according to the network loads. By simulation, the paper evaluates the performance of the scheme in terms of throughput, loss rate, average delay, and mean square error of synchronization. Numerical results show the effectiveness of the scheme.