Infrared image segmentation based on Otsu and genetic algorithm

The infrared image is formed by the thermal infrared rays of the targets and environment. As the targets radiate more heat, we can see they have larger grey-scale, locating in the top-end of histogram. According to this characteristic of infrared images, a new method for infrared image segmentation...

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Published in2011 International Conference on Multimedia Technology pp. 5421 - 5424
Main Authors Shunyong Zhou, Pingxian Yang
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.07.2011
Subjects
Genetic Algorithm
Genetic algorithms
Histograms
Image edge detection
Image segmentation
Infrared Image Segmentation
Noise
Otsu
Probability
Thermal engineering
Threshold
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ISBN1612847714
9781612847719
DOI10.1109/ICMT.2011.6003109

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Abstract The infrared image is formed by the thermal infrared rays of the targets and environment. As the targets radiate more heat, we can see they have larger grey-scale, locating in the top-end of histogram. According to this characteristic of infrared images, a new method for infrared image segmentation based on Otsu and genetic algorithm is proposed in this paper. First, covert the infrared image to grayscale image; Second, detect the image edge, and get the best threshold for image segmentation by Otsu and GA (Otsu-GA); Finally, Segment the image by the threshold, and contrast the results of two peaks and iteration. Experimental results show that the method effectively improved the quality of image segmentation.
AbstractList The infrared image is formed by the thermal infrared rays of the targets and environment. As the targets radiate more heat, we can see they have larger grey-scale, locating in the top-end of histogram. According to this characteristic of infrared images, a new method for infrared image segmentation based on Otsu and genetic algorithm is proposed in this paper. First, covert the infrared image to grayscale image; Second, detect the image edge, and get the best threshold for image segmentation by Otsu and GA (Otsu-GA); Finally, Segment the image by the threshold, and contrast the results of two peaks and iteration. Experimental results show that the method effectively improved the quality of image segmentation.
Author Shunyong Zhou
Pingxian Yang
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  surname: Pingxian Yang
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  organization: Dept. of Electron. Eng., Sichuan Univ. of Sci. & Eng., Zigong, China
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Snippet The infrared image is formed by the thermal infrared rays of the targets and environment. As the targets radiate more heat, we can see they have larger...
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SubjectTerms Genetic Algorithm
Genetic algorithms
Histograms
Image edge detection
Image segmentation
Infrared Image Segmentation
Noise
Otsu
Probability
Thermal engineering
Threshold
Title Infrared image segmentation based on Otsu and genetic algorithm
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