• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.8
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• pp.1423-1443
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• 2011

Background compensation plays an important role in detecting and isolating object motion in visual tracking. Here, we propose a Genetic Hough Transform, which combines the Hough Transform and Genetic Algorithm, as a method for eliminating background motion. Our method can handle cases in which the background may contain only a few, if any, feature points. These points can be used to estimate the motion between two successive frames. In addition to dealing with featureless backgrounds, our method can successfully handle motion blur. Experimental comparisons of the results obtained using the proposed method with other methods show that the proposed approach yields a satisfactory estimate of background motion.

• Proceedings of the Korean Information Science Society Conference
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• 1998.10c
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• pp.479-481
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• 1998

Noise가 있는 data에서 shape나 parameter를 찾았을 때 일반적으로 Hough transform이나 regression을 적용한다. Hough transform은 parameter space의 차수가 커지면 memory 문제가 존재하며, regression 모델은 한 개의 변수를 다른 변수의 함수로 가정하여 error를 최소화하여 데이터중 1 set의 parameter만 존재한다는 가정을 하여야 하는 문제점이 있다. 본 논문에서는 이러한 두 방법의 단점들을 보완하며, Fuzzy개념을 도입한 data fitting 방법을 제안하였다. 이 문제는 genetic algorithm을 도입하여 data를 Fuzzy membership을 갖는 것으로 가정한 최적화 문제로 해결하였다. 직선과 평면에 대한 실험 결과를 보인다.

• Journal of the Korea Society of Computer and Information
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• v.4 no.2
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• pp.95-104
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• 1999

With the increasing of cars, general studies of them for the traffic safety have been raised as important problems. Visual system to radio-controled driving is to sample road traffic information as reconstructing a model from lots of road traffic information which is successively input in order to drive on unknown road. This paper proposes a sampling process of the road traffic information board needed in automatic driving under automatic drive system using Hough Transform and Genetic Alorithm.