Shape-based infrared image leakage gas detection method

LIU Lumingen; ZHANG Yaozong; LUAN Lin; HONG Hanyu

doi:10.5768/JAO201940.0303002

Volume 40 Issue 3

May 2019

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LIU Lumingen, ZHANG Yaozong, LUAN Lin, HONG Hanyu. Shape-based infrared image leakage gas detection method[J]. Journal of Applied Optics, 2019, 40(3): 468-472. doi: 10.5768/JAO201940.0303002

Citation:

LIU Lumingen, ZHANG Yaozong, LUAN Lin, HONG Hanyu. Shape-based infrared image leakage gas detection method[J]. Journal of Applied Optics, 2019, 40(3): 468-472. doi: 10.5768/JAO201940.0303002

LIU Lumingen, ZHANG Yaozong, LUAN Lin, HONG Hanyu. Shape-based infrared image leakage gas detection method[J]. Journal of Applied Optics, 2019, 40(3): 468-472. doi: 10.5768/JAO201940.0303002

Citation:

LIU Lumingen, ZHANG Yaozong, LUAN Lin, HONG Hanyu. Shape-based infrared image leakage gas detection method[J]. Journal of Applied Optics, 2019, 40(3): 468-472. doi: 10.5768/JAO201940.0303002

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Shape-based infrared image leakage gas detection method

doi: 10.5768/JAO201940.0303002

1.
School of Electrical and Information Engineering, Wuhan Institute of Technology, Hubei Engineering Research Center of Video Image and HD Projection, Wuhan 430205, China
2.
Kuang-chi Institute of Advanced Technology, Shenzhen 518000, China

Received Date: 2018-10-10
Rev Recd Date: 2018-10-19
Publish Date: 2019-05-01

Abstract

Abstract

Aiming at the explosion and fire caused by leakage gas in industrial production, an infrared image leakage gas detection method based on shape and support vector machine(SVM) is proposed. The SVM classifier is trained by using the shape features of the infrared image sample of the leaking gas and the interfering object. The candidate target region is obtained by using the background difference-based motion detection for the infrared image sequence, and then the shape feature is extracted from the candidate target region, and finally the SVM classifier is used to obtain the final detection result. Experiments were carried out using ethylene gas leakage simulation data, and the detection rate was up to 98%. The results show that this method can effectively detect the leakage gas, which greatly reduces the false detection caused by the interference.
- leak gas detection,
- shape feature,
- support vector machine(SVM),
- infrared image

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References(15)

References

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