Comparative Evaluation of FPGA Implementation Alternatives for Real-Time Robust Ellipse Estimation based on RANSAC Algorithm

Theint Theint THU  Jimpei HAMAMURA  Rie SOEJIMA  Yuichiro SHIBATA  Kiyoshi OGURI  

IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences   Vol.E100-A   No.7   pp.1409-1417
Publication Date: 2017/07/01
Online ISSN: 1745-1337
DOI: 10.1587/transfun.E100.A.1409
Type of Manuscript: Special Section PAPER (Special Section on Design Methodologies for System on a Chip)
RANSAC,  FPGA,  Cramer's rule,  Gauss-Jordan elimination,  

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Field Programmable Gate Array (FPGA) based robust model fitting enjoys immense popularity in image processing because of its high efficiency. This paper focuses on the tradeoff analysis of real-time FPGA implementation of robust circle and ellipse estimations based on the random sample consensus (RANSAC) algorithm, which estimates parameters of a statistical model from a data set of feature points which contains outliers. In particular, this paper mainly highlights implementation alternatives for solvers of simultaneous equations and compares Gauss-Jordan elimination and Cramer's rule by changing matrix size and arithmetic processes. Experimental evaluation shows a Cramer's rule approach coupled with long integer arithmetic can reduce most hardware resources without unacceptable degradation of estimation accuracy compared to floating point versions.