8647579
MediaStation 5000: integrating video and audio
MediaStation 5000 is a highly integrated desktop multimedia system implemented on a single PC plug-in board. It performs multistandard compression, high-speed image processing, and fast 2D and 3D graphics functions. The Texas instruments Multimedia Video Processor (MVP), a single-chip multiprocessing device with a highly parallel internal architecture, provides the system's processing power and programmability.<<ETX>>
40331728
Efficient 2-D Convolution Algorithm with the Single-Data Multiple Kernel Approach
Abstract A fast implementation of convolution operation is described. The implementation takes advantage of various properties of commonly used kernels. First, the kernel elements are analyzed and rearranged, grouping the kernel elements of the same absolute value together and arranging trivial multiplication cases separately. Then the sequence of computing convolution sums is modified so that all the kernel elements could be multiplied by the same data element at each step. This new algorithm significantly reduces the number of multiplication operations for most widely used kernels. Our experiment shows that the performance improvement of two to seven over the direct implementation is achievable for most kernels. The required overhead (extra memory and preprocessing) is proportional to the kernel size and is negligible.
9437835
Computing Requirements of Modern Medical Diagnostic Ultrasound Machines
Abstract Ultrasound is one of the leading medical imaging modalities because it is safe, noninvasive, portable, easy to use, relatively inexpensive and displays images in real-time. Due to its real-time nature, an ultrasound machine must be able to process its incoming data quickly. High computational and throughput requirements in modern ultrasound machines have restricted their internal design to algorithm-specific hardware with limited programmability. Adding new ultrasound imaging applications or improving a machine's internal algorithms can require costly hardware redesigns and replacements of boards or of the entire machine. In an effort to address these problems, we have reviewed each of the essential functions in modern ultrasound machines and analyzed their computational requirements in programmable systems. These functions include dynamic downconversion, tissue signal processing, color flow processing, scan conversion, and tissue/flow decision. Our estimate of the total computing requirement to current ultrasound machines is 54.71 billion operations per second (BOPS) when transcendental functions are implemented in software and 31.26 BOPS when transcendental functions are implemented in lookup tables taking 160.26 Mbytes of memory. To investigate the feasibility of programmable generalized ultrasound systems, we have designed a flexible and parallel programmable ultrasound processing subsystem, called the Programmable Ultrasound Image Processor (PUIP). As the need for programmable ultrasound machines increases in the future due to various advantages (e.g., lower system cost, faster clinical use and lower research/development expenses), it will be crucial to develop not only a high-performance, scalable, reconfigurable parallel computer architecture meeting the computing requirement, but also efficient ultrasound algorithms that can be optimally mapped into the parallel architecture.
33400437
Facial Expression Recognition Using Active Appearance Model
This paper describes a facial expression recognition system based upon Active Appearance Model (AAM), which has been typically used for the face recognition task. Given that AAM has been also used in tracking the moving object, we thought it could be effective in recognizing the facial expressions of humans. Our results show that the performance of the facial expression recognition using AAM is reliably high when it combined with an enhanced Fisher classification model.
1232413
Secure group services for storage area networks
Storage Area Networks, with their ability to offer high data availability, reliability and scalability, are a promising solution for the large scale storage needs of many enterprises. As with any distributed storage system, a major design challenge for a Storage Area Network (SAN) is to provide data integrity and confidentiality. In this paper we propose a solution which addresses these core security requirements. In particular, we focus on mechanisms that enable efficient key distribution to allow scalable data sharing. Our scheme uses strong cryptographic techniques to achieve data security and integrity. Further, we delegate the bulk of the cryptographic processing to the SAN entities (e.g., switches, routers or other network elements), thereby removing bottlenecks at the disks and causing minimal inconvenience to the hosts. By recognizing the peer nature of the group of SAN entities, we propose efficient group key mechanisms that do not involve any centralized key distribution servers. This allows our scheme to be scalable and be free from any single point of failure or attack.
11956953
BioSilico: an integrated metabolic database system
BioSilico is a web-based database system that facilitates the search and analysis of metabolic pathways. Heterogeneous metabolic databases including LIGAND, ENZYME, EcoCyc and MetaCyc are integrated in a systematic way, thereby allowing users to efficiently retrieve the relevant information on enzymes, biochemical compounds and reactions. In addition, it provides well-designed view pages for more detailed summary information. BioSilico is developed as an extensible system with a robust systematic architecture.
14130132
Signal space detection for recording channels with jitter noise
A delay-constrained sequence detector is considered for recording channels whose major impediments include intersymbol interference (ISI) and magnetic transition jitter noise. The jitter noise is data-dependent, and a given noise sample is correlated with neighboring noise samples. A sequence detector with a finite decision delay can be formulated in a finite dimensional vector space. For a correlated noise channel, the decision boundary is generally quadratic. We present a technique for obtaining a minimal set of hyperplanes approximating a quadratic decision boundary with a negligible performance loss. In this process, a distance measure, which is consistent with the notion of the effective SNR, is defined and used as a design parameter to trade the complexity and performance. As an achievable performance bound, we derive the effective SNR for the maximum-likelihood sequence detector (MLSD) for these channels. The performance of the partial response maximum likelihood (PRML) detector commonly adopted for current data storage channels as well as the Viterbi algorithm (VA) based on the traditional Euclidean metric, which serves as the MLSD for additive white Gaussian noise, are also analyzed and compared with that of the proposed signal space detector.
7461874
Face and Facial Expression Recognition with an Embedded System for Human-Robot Interaction
In this paper, we present an embedded system in which face recognition and facial expression recognition for Human-Robot Interaction are implemented. To detect face with a fast and reliable way, AdaBoost algorithm is used. Then, Principal Component Analysis is applied for recognizing the face. Gabor wavelets are combined with Enhanced Fisher Model for facial expression recognition. Performance of the facial expression recognition reaches to 93%. The embedded system runs on 150MHz and the processing speed is 0.6 frames / second. Experimental result demonstrates that face detection, recognition and facial expression can be implemented with an embedded system for the Human-Robot Interaction.