Parallel Computing System for Image Intelligent Processing

Parallel computing in digital image processing

Application with sequential algorithm can no longer rely on technology scaling to improve performance. Image processing applications exhibits high degree of parallelism and are excellent source for multi-core platform. Major challenge of parallel processing is not only aim to high performance but is to give solution in less time and better utilization of resources. Medical imaging require more ...

Parallel Processing and Bio-inspired Computing for Biomedical Image Registration

Image Registration (IR) is an optimization problem computing optimal parameters of a geometric transform used to overlay one or more source images to a given model by maximizing a similarity measure. In this paper the use of bio-inspired optimization algorithms in image registration is analyzed. Results obtained by means of three different algorithms are compared: Bacterial Foraging Optimizatio...

KAIST image computing system (KICS): A parallel architecture for real-time multimedia data processing

An ecient parallel architecture is proposed for high-performance multimedia data processing using multiple multimedia video processors (MVP; TMS320C80), which are fully programmable general digital signal processors (DSP). This paper describes several requirements for a multimedia data processing system and the system architecture of an image computing system called the KAIST Image Computing S...

Intelligent Image Processing Framework

Parallel image processing in heterogeneous computing network systems

We present a uniform construct of parallel programming for a set of image processing tasks based on our Distributed Computing Primitive (DCP) concept. Our target architecture is a heterogeneous computing network system consisting of various high performance workstations connected through a local area network. We show that DCP has advantages over non-primitive PVM-based parallel approaches in th...