A real-time multi-scale 2D Gaussian filter based on FPGA

Haibo Luo; Xingqin Gai; Zheng Chang; Bin Hui

doi:10.1117/12.2072284

24 November 2014 A real-time multi-scale 2D Gaussian filter based on FPGA

Haibo Luo, Xingqin Gai, Zheng Chang, Bin Hui

Proceedings Volume 9301, International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition; 930104 (2014) https://doi.org/10.1117/12.2072284
Event: International Symposium on Optoelectronic Technology and Application 2014, 2014, Beijing, China

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.

Citation Download Citation

Haibo Luo, Xingqin Gai, Zheng Chang, and Bin Hui "A real-time multi-scale 2D Gaussian filter based on FPGA", Proc. SPIE 9301, International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 930104 (24 November 2014); https://doi.org/10.1117/12.2072284

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