Abstract

Image segmentation is a computationally expensive and complex task that continuously focuses on performance challenges due to tremendous increase in the volume of high resolution images. Nowadays, shared memory multicore parallel programming architectures using OpenMP is emerging as an attractive computing platform for both general purpose and scientific computations due to their immense processing performance, less complexity and minimal cost. Faster execution of image segmentation process is emerging as an important criterion with the technical advancements in multicore architectures. This paper proposes an experimental method for parallelizing wavelet based image segmentation using OpenMP. Emphasis is also made on exploring the computational data and task parallelism in wavelet based image segmentation using OpenMP on shared memory architecture with promising processing speed and accurate segmentation result.

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