Parallelizing connectivity-based image processing operators in a multi-core environment

Abstract

With increasing computational requirements for state-of-art computer vision and graphics algorithms, multi-core processor implementations have picked up momentum. Adapting single core image processing algorithms for multi-core environment is difficult. Different platforms require a hand tailored approach to optimally fit the algorithm into a given multi-core architecture. An automatic compiler which could split and compile the code for any platform is desirable. Such a compiler doesn't exist and this kind of automation is tough to achieve. To aid existing compilers, we propose a simple software architecture framework for multi-core systems that aims to provide a uniform, scalable, and portable solution, solving specifically for connectivity based image processing operators.