Threshold segmentation algorithm for infrared small target in agriculture and forestry fire
A novel image segmentation for infrared small target of agriculture and forestry fire is proposed in this paper. Usually, Maximum Variance Image Segmentation method (Otsu) is a popular non-parametric method in image segmentation. However, it needs a lot computation and has poor real-time quality. Th...
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| Vydané v: | Chinese Control Conference s. 4020 - 4025 |
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| Hlavní autori: | , , |
| Médium: | Konferenčný príspevok.. Journal Article |
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01.07.2016
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| ISSN: | 1934-1768 |
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| Abstract | A novel image segmentation for infrared small target of agriculture and forestry fire is proposed in this paper. Usually, Maximum Variance Image Segmentation method (Otsu) is a popular non-parametric method in image segmentation. However, it needs a lot computation and has poor real-time quality. Thus it is hard to be wide applied in many situations. To over come this issue, a constructive approach to obtain optimal threshold of between-class variance as fitness function for Otsu by particle swarm optimization (PSO), reduce the amount of computation and improve real-time performance. The performance of the proposed method is evaluated through infrared small target of agriculture and forestry fire. The experimental results demonstrate the effectiveness of the proposed method. |
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| AbstractList | A novel image segmentation for infrared small target of agriculture and forestry fire is proposed in this paper. Usually, Maximum Variance Image Segmentation method (Otsu) is a popular non-parametric method in image segmentation. However, it needs a lot computation and has poor real-time quality. Thus it is hard to be wide applied in many situations. To over come this issue, a constructive approach to obtain optimal threshold of between-class variance as fitness function for Otsu by particle swarm optimization (PSO), reduce the amount of computation and improve real-time performance. The performance of the proposed method is evaluated through infrared small target of agriculture and forestry fire. The experimental results demonstrate the effectiveness of the proposed method. |
| Author | Wang, Yuchao Lin, Dehua Fu, Huixuan |
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| Snippet | A novel image segmentation for infrared small target of agriculture and forestry fire is proposed in this paper. Usually, Maximum Variance Image Segmentation... |
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| SubjectTerms | Agriculture Clustering algorithms Computation Fire recognition Fires Forestry Image segmentation Infrared image Otsu Particle swarm optimization Signal processing algorithms Swarm intelligence Thresholds Variance |
| Title | Threshold segmentation algorithm for infrared small target in agriculture and forestry fire |
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