Statistical pattern recognition for real-time image edge detection on FPGA

Author

Ziyan Liu ; Jia Qi ; Liang Feng ; Li Feng

Author_Institution

Coll. of Electron. & Inf., Guizhou Univ., Guiyang, China

fYear

2014

fDate

19-23 Oct. 2014

Firstpage

880

Lastpage

886

Abstract

Image edge detection is a fundamental process in computer vision. Image edges represent the major fraction of information in an image. Traditional edge-detection techniques focus on the gradient calculation method. In this paper, for the first time, the statistical pattern recognition method is used to detect the edge after the real-time image was processed via the median filtering method and implemented on FPGA. In comparison to the Sobel algorithm, the proposed method has superior anti-noise capability.

Keywords

computer vision; edge detection; field programmable gate arrays; gradient methods; image denoising; image representation; median filters; statistical analysis; FPGA; antinoise capability; computer vision; gradient calculation method; information representation; median filtering method; real-time image edge detection; statistical pattern recognition method; Feature extraction; Field programmable gate arrays; Filtering; Hardware; Image edge detection; Pattern recognition; Real-time systems; FPGA; Median Filtering; Real-Time Image Edge Detection; Statistical Pattern Recognition;

fLanguage

English

Publisher

ieee

Conference_Titel

Signal Processing (ICSP), 2014 12th International Conference on

Conference_Location

Hangzhou

ISSN

2164-5221

Print_ISBN

978-1-4799-2188-1

Type

conf

DOI

10.1109/ICOSP.2014.7015130

Filename

7015130