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.
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.
10239106
Programmable ultrasound imaging using multimedia technologies: a next-generation ultrasound machine
High computational and throughput requirements in modern ultrasound machines have restricted their internal design to algorithm-specific hardware with limited programmability. The authors have architected a programmable ultrasound processing system, Programmable Ultrasound Image Processor (PUIP), to facilitate engineering and clinical ultrasound innovations. Multiple high-performance multimedia processors were used to provide a computing power of 4 billion operations per second. Flexibility was achieved by making the system programmable and multimodal, e.g., B-mode, color flow, cine and Doppler data can be processed. They have successfully designed and implemented the PUIP to fit within an ultrasound machine. It provides a platform for rapid testing of new concepts in ultrasound processing and enables software upgrades for future technologies. Current and future clinical applications include extended fields of view, quantitative measurements, three-dimensional ultrasound reconstruction and visualization, adaptive persistence, speckle reduction, edge enhancement, image segmentation, and motion analysis. The PUIP is a significant step in the evolution of ultrasound machines toward more flexible and generalized systems bridging the gap between many innovative ideas and their clinical use in ultrasound machines.
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.
18367763
Business process integration with Web services
Web services facilitate the creation of business process solutions in an efficient, standard way. The process solutions development with Web services requires the automation of discovery and composition of Web services. In this paper, we focus on the discovery of Web services based on the capabilities and properties of published services, and the composition of processes based on the requirements of submitted requests. We propose a solution which comprises multiple matching algorithms, first, a micro-level matching algorithm which matches the capabilities of services with activities in a process request, and, second, macro-level matching algorithms which are used to compose a business process by identifying services that satisfy the business requirements and constraints of the request. The solution from the macro-level matching algorithms is optimal in terms of meeting a certain business objective, e.g., minimizing the cost or execution time, or maximizing the total utility value of business properties of interest.
35466192
Scheduling on parallel identical machines to minimize total tardiness
This paper focuses on the problem of scheduling n independent jobs on m identical parallel machines for the objective of minimizing total tardiness of the jobs. We develop dominance properties and lower bounds, and develop a branch and bound algorithm using these properties and lower bounds as well as upper bounds obtained from a heuristic algorithm. Computational experiments are performed on randomly generated test problems and results show that the algorithm solves problems with moderate sizes in a reasonable amount of computation time. � 2005 Elsevier B.V. All rights reserved.
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.
6168983
Privacy Preserving Nearest Neighbor Search
Data mining is frequently obstructed by privacy concerns. In many cases data is distributed, and bringing the data together in one place for analysis is not possible due to privacy laws (e.g. HIPAA) or policies. Privacy preserving data mining techniques have been developed to address this issue by providing mechanisms to mine the data while giving certain privacy guarantees. In this work we address the issue of privacy preserving nearest neighbor search, which forms the kernel of many data mining applications. To this end, we present a novel algorithm based on secure multiparty computation primitives to compute the nearest neighbors of records in horizontally distributed data. We show how this algorithm can be used in three important data mining algorithms, namely LOF outlier detection, SNN clustering, and kNN classification
47302704
On the performance of group key agreement protocols
Group key agreement (GKA) is a fundamental building block for securing peer group communication systems (GCS). Several group key agreement protocols were proposed in the past, all assuming an underlying group communication infrastructure. This paper presents a performance evaluation of 5 notable GKA protocols integrated with a reliable group communication system (Spread). They are: centralized group key distribution (CKD), Burmester-Desmedt (BD), Steer et al. (STR), group Diffie-Hellman GDH) and tree-based group Diffie-Hellman (TGDH).. We present concrete results obtained in experiments on local- and wide-area networks. Our analysis of these results offers insights into their relative scalability and practicality.