13345946
Efficient Implementation of Image Warping on a Multimedia Processor
The spatial transformation of images, commonly known as image warping, is fundamental to many applications, e.g. remote sensing, medical imaging, computer vision, and computer graphics. Computational demands in image warping are high, requiring a geometric transformation, address and coefficient generation, and some form of interpolation. However, unlike most image processing algorithms, the data flow for image warping can be highly irregular, which makes any efficient implementation challenging.This paper describes an efficient algorithm which addresses these challenges by making use of the capabilities of a single-chip multiprocessing microprocessor, the Texas Instruments TMS320C80 MVP (multimedia video processor). the MVP's advanced digital signal processors (ADSPs) offer tremendous computational power through instruction-level parallelism and several key features designed for image processing. The MVP's intelligent input/output interface via the transfer controller (TC) permits efficient irregular memory accesses.Affine and perspective warps have been implemented for 8-bit, 16-bit and and RGB color data using bilinear interpolation.The affine warp can generate 512 × 512 warped output images faster than real-time video rates require. For 8-bit images, the performance is 14.1 ms. Although the amount of computation necessary is the same for 16-bit images, the execution time increases to 15.2 ms since twice as many bytes need to be transferred. For RGB color images, it takes 28.0 ms. The perspective warp requires 46.3 ms for 8-bit and 16-bit images, and 60.4 ms for RGB color images. This unprecedented performance for software-based image warping exceeds many hardware approaches reported in the literature.
16063207
Using motion-compensated frame-rate conversion for the correction of 3: 2 pulldown artifacts in video sequences
Currently, the most popular method of converting 24 frames per second (fps) film to 60 fields/s video is to repeat each odd-numbered frame for 3 fields and each even-numbered frame for 2 fields. This method is known as 3:2 pulldown and is an easy and inexpensive way to perform 24 fps to 60 fields/s frame-rate conversion. However, the 3:2 pulldown introduces artifacts, which are especially visible when viewing on progressive displays and during slow-motion playback. We have developed a motion-compensated frame-rate conversion algorithm to reduce the 3:2 pulldown artifacts. By using frame-rate conversion with interpolation instead of field repetition, mean square error and blocking artifacts are reduced significantly. The techniques developed here can also be applied to the general frame-rate conversion problem.
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>>
12493055
A methodology for evaluation of boundary detection algorithms on medical images
Image segmentation is the partition of an image into a set of nonoverlapping regions whose union is the entire image. The image is decomposed into meaningful parts which are uniform with respect to certain characteristics, such as gray level or texture. In this paper, we propose a methodology for evaluating medical image segmentation algorithms wherein the only information available is boundaries outlined by multiple expert observers. In this case, the results of the segmentation algorithm can be evaluated against the multiple observers' outlines. We have derived statistics to enable us to find whether the computer-generated boundaries agree with the observers' hand-outlined boundaries as much as the different observers agree with each other. We illustrate the use of this methodology by evaluating image segmentation algorithms on two different applications in ultrasound imaging. In the first application, we attempt to find the epicardial and endocardial boundaries from cardiac ultrasound images, and in the second application, our goal is to find the fetal skull and abdomen boundaries from prenatal ultrasound images.
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.
809949
Pubic arch detection in transrectal ultrasound guided prostate cancer therapy
New biopsy techniques, increased life expectancy, and prostate-specific antigen (PSA) screening have contributed to an increase in the reported incidence of prostate cancer. Among several treatment options available to the patients, transperineal prostate brachytherapy has emerged as a medically successful, cost-effective outpatient procedure for treating localized prostate cancer. Transperineal prostate brachytherapy employs transrectal ultrasound (TRUS) as the primary imaging modality to accurately preplan and subsequently execute the placement of radioactive seeds into the prostate. Under TRUS guidance, a needle (preloaded with radioactive seeds) is inserted through a template guide, through the perineum and into a predetermined prostate target. The pubic arch, formed by the central union of pelvic bones, is a potential barrier to the passage of these needles in the prostate. A critical aspect, therefore, in the planning and execution of the brachytherapy procedure is the accurate assessment of pubic arch interference (PAI) in relation to the prostate. Traditionally, the evaluation of PAI has involved computed tomography correlate scanning or crude subjective evaluations. In this paper, the authors describe a new method of assessing PAI by detecting the pubic arch via image processing on the TRUS images. The PAI detection (PAID) algorithm first uses a technique known as sticks to selectively enhance the contrast of linear features in ultrasound images. Next, the enhanced image is thresholded via percentile thresholding. Finally, the authors fit a parabola (a model for the pubic arch) recursively to the thresholded image. Their evaluation result from 15 cases indicates that the algorithm can successfully detect the pubic arch with 90% accuracy. Based on this study, the authors believe that detecting the pubic arch and assessing PAI can be done practically and more accurately in the clinical setting using TRUS rather than the current available methods.
2299968
Multi-campaign Assignment Problem and Optimizing Lagrange Multipliers
Customer relationship management is crucial in acquiring and maintaining royal customers. To maximize revenue and customer satisfaction, companies try to provide personalized services for customers. A representative effort is one-to-one marketing. The fast development of Internet and mobile communication boosts up the market of one-to-one marketing. A personalized campaign targets the most attractive customers with respect to the subject of the campaign. So it is important to expect customer preferences for campaigns. Collaborative Filtering (CF) and various data mining techniques are used to expect customer preferences for campaigns. Especially, since CF is fast and simple, it is widely used for personalization in e-commerce. There have been a number of customer-preference estimation methods based on CF. As personalized campaigns are frequently performed, several campaigns often happen to run simultaneously. It is often the case that an attractive customer for a specific campaign tends to be attractive for other campaigns. If we perform separate campaigns without considering this problem, some customers may be bombarded by a considerable number of campaigns. We call this overlapped recommendation problem. The larger the number of recommendations for a customer, the lower the customer interest for campaigns. In the long run, the customer response for campaigns drops. It lowers the marketing efficiency as well as customer satisfaction. Unfortunately, traditional methods only focused on the effectiveness of a single campaign and did not consider the problem with respect to the overlapped recommendations. In this paper, we define the multi-campaign assignment problem (MCAP) considering the overlapped recommendation problem and propose a number of methods for the issue including a genetic approach. We also verify the effectiveness of the proposed methods with field data.
8097408
Combating Double-Spending Using Cooperative P2P Systems
An electronic cash system allows users to withdraw coins, represented as bit strings, from a bank or broker, and spend those coins anonymously at participating merchants, so that the broker cannot link spent coins to the user who withdraws them. A variety of schemes with various security properties have been proposed for this purpose, but because strings of bits are inherently copyable, they must all deal with the problem of double-spending. In this paper, we present an electronic cash scheme that introduces a new peer-to-peer system architecture to prevent double-spending without requiring an on-line trusted party or tamper-resistant software or hardware. The scheme is easy to implement, computationally efficient, and provably secure. To demonstrate this, we report on a proof-of-concept implementation for Internet vendors along with a detailed complexity analysis and selected security proofs.
28723686
Implementation of ECC/ECDSA cryptography algorithms based on Java card
This paper describes the implementations and test results of elliptic curve cryptography (ECC) and elliptic curve digital signature algorithm (ECDSA) algorithms based on Java card. A 163-bit ECC guarantees as secure as the 1024-bit Rivest-Shamir-Adleman (RSA) public key algorithm, which has been frequently used until now. According to our test results, the 163-bit ECC processing time is about five times faster compared with the 1024-bit RSA, and the amount of resource usages of ECC is smaller than RSA. Therefore, ECC is more appropriate for use on secure devices such as smart cards and wireless devices with constrained computational power consumption and memory resources.
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.
17676271
Ontology Modeling and Storage System for Robot Context Understanding
A mobile robot that interacts with its environment needs a machine-understandable representation of objects and their usages. We present an ontology of objects, with generic shape representations obtained through form-function reasoning. Sets of objects are associated with typical human activities, which supports context understanding. We describe an efficient ontology document storage system, which is based on stable and well-known relational databases. We first design a relational data schema appropriate for Web Ontology Language (OWL) documents, and then develop a transformation mechanism from OWL documents to the relational schema.