Pests detecting is an important research subject in grain storage field.In the past decades,many edge detection methods have been applied to the edge detection of stored grain pests.Although some of them can realize t...Pests detecting is an important research subject in grain storage field.In the past decades,many edge detection methods have been applied to the edge detection of stored grain pests.Although some of them can realize the stored grain pests detecting,precision and robustness are not good enough.Spectral residual(SR)saliency edge detection defines the logarithmic spectrumof image as novelty part of the image information.The remaining spectrumis converted to the airspace to obtain edge detection results.SR algorithm is completely based on frequency domain processing.It not only can effectively simplify the target detection algorithm,but also can improve the effectiveness of target recognition.The experimental results show that the edge results of stored grain pests detected by SR method are effective and stable.展开更多
Xinjiang Uygur Autonomous Region is a scarcely populated area in China and technicians for plant protection are extremely deficient.The occurrence areas of insect pests in grain and cotton crops have been increasing y...Xinjiang Uygur Autonomous Region is a scarcely populated area in China and technicians for plant protection are extremely deficient.The occurrence areas of insect pests in grain and cotton crops have been increasing year by year, causing serious economic losses. Aiming for several main grain and economic crops of Xinjiang(cotton, corn and wheat), an intelligence decision support system for diagnosis and management of grain and cotton crop pests in Xinjiang was designed and developed, which was based on android platform and windows system architecture. APP application program of smart phones was used as an implementation form. The intelligence decision support system will help plant protection personnel and farmers to solve local pest recognition and prevention control problem at the grassroots level in Xinjiang remote regions.展开更多
In order to achieve the acoustic signal distributed acquisition of stored grain pests, a novel acoustic signal acquisition system was presented based on the wireless sensor networks. And the system architecture, hardw...In order to achieve the acoustic signal distributed acquisition of stored grain pests, a novel acoustic signal acquisition system was presented based on the wireless sensor networks. And the system architecture, hardware configuration, and software were introduced in detail. Considering bandwidth limitation of wireless sensor networks, random sampling algorithm based on the compressed sensing theory was proposed. The developed acoustic signal acquisition system was applied in sampling the crawl acoustic signal of Tribolium castaneum Herbst adults in granary. Preliminary experimentation indicated the rationality and practicability of the developed system and the proposed algorithm. They can implement the remote, real-time, and reliable wireless transmission for the acoustic signal sampled data of multiple points stored grain pests effectively.展开更多
基金financially supported by National Natural Science Foundation of China(No.61871176)Key Scientific and Technological Project of Science and Technology Department of Henan Province(No.172102210030,182102110099)+2 种基金Key Scientific Research Project Program of Universities of Henan Province(No.18B520025)Open Fund of Key Laboratory of Grain Information Processing and Control(No.KFJJ-2018-102)supported by Collaborative Innovation Center of Grain Storage and Security of Henan Province
文摘Pests detecting is an important research subject in grain storage field.In the past decades,many edge detection methods have been applied to the edge detection of stored grain pests.Although some of them can realize the stored grain pests detecting,precision and robustness are not good enough.Spectral residual(SR)saliency edge detection defines the logarithmic spectrumof image as novelty part of the image information.The remaining spectrumis converted to the airspace to obtain edge detection results.SR algorithm is completely based on frequency domain processing.It not only can effectively simplify the target detection algorithm,but also can improve the effectiveness of target recognition.The experimental results show that the edge results of stored grain pests detected by SR method are effective and stable.
基金Supported by National Natural Science Foundation of China "Characterization and RNAi Silencing of Detoxification Gene Families in Cotton Mite"(31560532)
文摘Xinjiang Uygur Autonomous Region is a scarcely populated area in China and technicians for plant protection are extremely deficient.The occurrence areas of insect pests in grain and cotton crops have been increasing year by year, causing serious economic losses. Aiming for several main grain and economic crops of Xinjiang(cotton, corn and wheat), an intelligence decision support system for diagnosis and management of grain and cotton crop pests in Xinjiang was designed and developed, which was based on android platform and windows system architecture. APP application program of smart phones was used as an implementation form. The intelligence decision support system will help plant protection personnel and farmers to solve local pest recognition and prevention control problem at the grassroots level in Xinjiang remote regions.
文摘In order to achieve the acoustic signal distributed acquisition of stored grain pests, a novel acoustic signal acquisition system was presented based on the wireless sensor networks. And the system architecture, hardware configuration, and software were introduced in detail. Considering bandwidth limitation of wireless sensor networks, random sampling algorithm based on the compressed sensing theory was proposed. The developed acoustic signal acquisition system was applied in sampling the crawl acoustic signal of Tribolium castaneum Herbst adults in granary. Preliminary experimentation indicated the rationality and practicability of the developed system and the proposed algorithm. They can implement the remote, real-time, and reliable wireless transmission for the acoustic signal sampled data of multiple points stored grain pests effectively.
