Image Segmentation Using OpenMP and Its Application in Plant Species Classification

Abdul Rahman, Mohd Nordin and Mamat, Abd. Rasid and Mat, Nashriyah (2015) Image Segmentation Using OpenMP and Its Application in Plant Species Classification. International Journal of Software Engineering and Its Applications, 9 (5). pp. 135-144. ISSN 1738-9984

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Abstract

Segmentation is very important in early stage of image processing pipelines. Final results of image processing are strongly depending on the initial image segmentation quality. A good quality result often comes at the price of high computational cost including computation speed. Image segmentation requires long computation task caused by sequential processing of huge sizes of image and complex tasks. Nowadays, multi-core architectures are emerging as an attractive platform for parallel processing because it has two or more independent cores in a single physical package and their comparatively low cost. In this paper, two parallelization strategies (fine-grain and coarse-grain approach) are proposed for computing leaf image segmentation. The Canny Edge Detector and Otsu thresholding methods are used due to their wide range of usage for leaf segmentation in plant classification. The implementation is developed under multi-core architecture with shared memory multiprocessors. The OpenMP (Open Multi-Processing), an API (Application Programming Interface) is utilized for writing multi-threaded applications in shared memory architecture. The comparative study with two parallelization strategies is discussed further in this paper.

Item Type: Article
Keywords: Image processing, image segmentation, parallel processing, OpenMP, leaf shape based classification
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Faculty / Institute: Faculty of Informatics & Computing
Depositing User: Dr Mohd Nordin Abdul Rahman
Date Deposited: 12 Jul 2015 02:38
Last Modified: 12 Jul 2015 02:38
URI: http://erep.unisza.edu.my/id/eprint/3456

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