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

• 作者: Qifu Wang Suping Yu Yanli Wu Yao Qin
• 来源期刊: 粮油科技:英文版
• 学科: 工学
• 关键词: Stored GRAIN PESTS SALIENCY DETECTION Spectral RESIDUAL (SR) Edge DETECTION
• 年，卷（期）: 2019,（2）
• 页码范围: 33-38
• 页数: 6页
• 分类号: TN9

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.