@article{Lee2011,
	title = {Automatic thresholding selection for image segmentation based on genetic algorithm},
	volume = {17},
	issn = {19765622},
	url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-84861172295%7B%5C&%7DpartnerID=MN8TOARS},
	doi = {10.5302/J.ICROS.2011.17.6.587},
	abstract = {In this paper, we focus on the issue of automatic selection for multi-level threshold, and we greatly improve the efficiencyof Otsu's method for image segmentation based on genetic algorithm. We have investigated and evaluated the performance of theOtsu and Valley-emphasis threshold methods. Based on this observation we propose a method for automatic threshold method thatsegments an image into more than two regions with high performance and processing in real-time. Our paper introduced new peakdetection, combines with evolution algorithm using MAGA (Modified Adaptive Genetic Algorithm) and HCA (Hill ClimbingAlgorithm), to find the best threshold automatically, accurately, and quickly. The experimental results show that the proposedevolutionary algorithm achieves a satisfactory segmentation effect and that the processing time can be greatly reduced when thenumber of thresholds increases. © ICROS 2011.},
	number = {6},
	journal = {Journal of Institute of Control, Robotics and Systems},
	author = {Lee, Byung Ryong and Truong, Quoc Bao and Pham, Van Huy and Kim, Hyoung Seok},
	month = jun,
	year = {2011},
	keywords = {Automatic threshold, Genetic algorithm, Image segmentation, Otsu's method, Valley-emphasis method},
	pages = {587--595},
}

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Our paper introduced new peakdetection, combines with evolution algorithm using MAGA (Modified Adaptive Genetic Algorithm) and HCA (Hill ClimbingAlgorithm), to find the best threshold automatically, accurately, and quickly. 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We have investigated and evaluated the performance of theOtsu and Valley-emphasis threshold methods. Based on this observation we propose a method for automatic threshold method thatsegments an image into more than two regions with high performance and processing in real-time. Our paper introduced new peakdetection, combines with evolution algorithm using MAGA (Modified Adaptive Genetic Algorithm) and HCA (Hill ClimbingAlgorithm), to find the best threshold automatically, accurately, and quickly. 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