Mallegowda, M., and Karthik, N. and Anvith, A. (2023) Serial and Parallel Computation of Bone Scan Image Processing. Proceedings of the International Conference on Innovative Computing & Communication (ICICC) 2022.
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4361148
https://doi.org/10.2139/ssrn.4361148

has been cited by the following article:

• TITLE: Parallel Technologies with Image Processing Using Inverse Filter

  AUTHORS: Rahaf Alsharhan, Areej Muheef, Yasmin Al Ibrahim, Afnan Rayyani, Yasir Alguwaifli

  KEYWORDS: Parallel, Parallelization, Image Processing, Inverse Filtering, OpenMP, Race Conditions

  JOURNAL NAME: Journal of Computer and Communications, Vol.12 No.1, January 29, 2024

  ABSTRACT: Real-time capabilities and computational efficiency are provided by parallel image processing utilizing OpenMP. However, race conditions can affect the accuracy and reliability of the outcomes. This paper highlights the importance of addressing race conditions in parallel image processing, specifically focusing on color inverse filtering using OpenMP. We considered three solutions to solve race conditions, each with distinct characteristics: #pragma omp atomic: Protects individual memory operations for fine-grained control. #pragma omp critical: Protects entire code blocks for exclusive access. #pragma omp parallel sections reduction: Employs a reduction clause for safe aggregation of values across threads. Our findings show that the produced images were unaffected by race condition. However, it becomes evident that solving the race conditions in the code makes it significantly faster, especially when it is executed on multiple cores.