Color image edge detection based on quantity of color information and implementation on the GPU.

Zhao, J.; Xiang, Y.; Dawson, L.; Stewart, I.A.

Abstract

In this paper, we present a new method for quantifying color information so as to detect edges in color images. Our method uses the volume of a pixel in the HSI color space, allied with noise reduction, thresholding and edge thinning. We implement our algorithm using NVIDIA Compute Unified Device Architecture (CUDA) for direct execution on Graphics Processing Units (GPUs). Our experimental results show that: compared to traditional edge detection methods, our method can improve the accuracy of edge detection and withstand greater levels of noise in images; and our GPU implementation achieves speedups over related CUDA implementations.

Citation

Zhao, J., Xiang, Y., Dawson, L., & Stewart, I. (2011, December). Color image edge detection based on quantity of color information and implementation on the GPU. Presented at 23rd IASTED International Conference on Parallel and Distributed Computing and Systems, PDCS'11., Dallas, USA

• Presentation Conference Type: Conference Paper (published)
• Conference Name: 23rd IASTED International Conference on Parallel and Distributed Computing and Systems, PDCS'11.
• Publication Date: 2011
• Deposit Date: Oct 5, 2011
• Pages: 116-123
• Book Title: Proceeding (757) Parallel and Distributed Computing and Systems - 2011, December 14 – 16, 2011, Dallas, USA.
• DOI: https://doi.org/10.2316/p.2011.757-077
• Keywords: color image edge detection, HSI color space, GPU
• Public URL: https://durham-repository.worktribe.com/output/1157756