UMP Institutional Repository

Parallel guided image processing model for ficus deltoidea (Jack) moraceae varietal recognition

Ahmad Fakhri, Ab. Nasir and Ahmad Shahrizan, Abdul Ghani and M. Nordin, A. Rahman (2018) Parallel guided image processing model for ficus deltoidea (Jack) moraceae varietal recognition. In: Intelligent Manufacturing & Mechatronics: Proceedings of Symposium, 29 January 2018, Pekan, Pahang, Malaysia. Lecture Notes in Mechanical Engineering . Springer Singapore, Singapore, pp. 487-503. ISBN 9789811087875

[img] Pdf
book52 Parallel guided image processing model for ficus deltoidea (Jack) moraceae varietal recognition.pdf
Restricted to Repository staff only

Download (373kB) | Request a copy
[img]
Preview
Pdf
book52.1 Parallel guided image processing model for ficus deltoidea (Jack) moraceae varietal recognition.pdf

Download (138kB) | Preview

Abstract

Nowadays, with the huge number of leaves data, plant species recognition process becomes computationally expensive. Many computer scientists have suggested that the usage of parallel and distributed computing should be strongly considered as mandatory for handling computationally intensive programs. The availability of high performance multi-cores architecture results the complex recognition system to become popular in parallel computing area. This paper emphasizes on the computational flow design to enable the execution of the complex image processing tasks for Ficus deltoidea varietal recognition to be processed on parallel computing environment. Multi-cores computer is used whereas one of them acts as a master processor of the process and the other remaining processors act as worker processors. The master processor responsibles for controlling the main system operations such as data partitioning, data allocation, and data merging which results from worker processors. Experiments showed that a multi-cores parallel environment is a very appropriate platform for pipeline image processing. From the results, the sequential complex image processing model and computational flow design are significantly improved when executed through parallel model under multi-cores computer system. As the number of cores increases, the computational time taken by the parallel algorithm becomes less.

Item Type: Book Section
Additional Information: Index by Scopus
Uncontrolled Keywords: Ficus deltoidea jack; Plant species recognition; Image processing; SPMD architecture; Parallel computing
Subjects: T Technology > TS Manufactures
Faculty/Division: Faculty of Manufacturing Engineering
Depositing User: Pn. Hazlinda Abd Rahman
Date Deposited: 06 Aug 2018 03:01
Last Modified: 06 Aug 2018 03:01
URI: http://umpir.ump.edu.my/id/eprint/21748
Download Statistic: View Download Statistics

Actions (login required)

View Item View Item