Method for pests detecting in stored grain based on spectral residual saliency edge detection  

作　　者：Yao Qin Yanli Wu Qifu Wang Suping Yu 

机构地区：[1]College of Information Science and Engineering,Henan University of Technology,Zhengzhou 450001,China [2]Key Laboratory of Grain Information Processing and Control,Henan University of Technology,Ministry of Education,Zhengzhou 450001,China [3]Henan Academy of Science,Applied Physics Institute Co.,Ltd,Zhengzhou 450001,China [4]Luoyang Institute of Science and Technology,Department of Computer and Information Engineering,Luoyang 471000,China

出　　处：《Grain & Oil Science and Technology》2019年第2期33-38,共6页粮油科技（英文版）

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);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

摘　　要：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.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 spectrum of image as novelty part of the image information. The remaining spectrum is 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.

关 键 词：Stored GRAIN PESTS SALIENCY DETECTION Spectral RESIDUAL (SR) Edge DETECTION 

分 类 号：TN9[电子电信—信息与通信工程]