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Proceedings Paper

A real-time multi-scale 2D Gaussian filter based on FPGA
Author(s): Haibo Luo; Xingqin Gai; Zheng Chang; Bin Hui
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Paper Abstract

Multi-scale 2-D Gaussian filter has been widely used in feature extraction (e.g. SIFT, edge etc.), image segmentation, image enhancement, image noise removing, multi-scale shape description etc. However, their computational complexity remains an issue for real-time image processing systems. Aimed at this problem, we propose a framework of multi-scale 2-D Gaussian filter based on FPGA in this paper. Firstly, a full-hardware architecture based on parallel pipeline was designed to achieve high throughput rate. Secondly, in order to save some multiplier, the 2-D convolution is separated into two 1-D convolutions. Thirdly, a dedicate first in first out memory named as CAFIFO (Column Addressing FIFO) was designed to avoid the error propagating induced by spark on clock. Finally, a shared memory framework was designed to reduce memory costs. As a demonstration, we realized a 3 scales 2-D Gaussian filter on a single ALTERA Cyclone III FPGA chip. Experimental results show that, the proposed framework can computing a Multi-scales 2-D Gaussian filtering within one pixel clock period, is further suitable for real-time image processing. Moreover, the main principle can be popularized to the other operators based on convolution, such as Gabor filter, Sobel operator and so on.

Paper Details

Date Published: 24 November 2014
PDF: 7 pages
Proc. SPIE 9301, International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 930104 (24 November 2014); doi: 10.1117/12.2072284
Show Author Affiliations
Haibo Luo, Shenyang Institute of Automation (China)
Univ. of Chinese Academy of Sciences (China)
Xingqin Gai, Hebei Hanguang Industry Co., Ltd. (China)
Zheng Chang, Shenyang Institute of Automation (China)
Bin Hui, Shenyang Institute of Automation (China)

Published in SPIE Proceedings Vol. 9301:
International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition
Gaurav Sharma; Fugen Zhou; Jennifer Liu, Editor(s)

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