Identifying and counting phyllotreta striolata fabriciuson based on yellow sticky trap [基于黄色诱捕板的黄曲条跳甲识别与计数方法]

作者：Zhang L.; Zhang C.; Cen G.; Gao Y.^*

来源：Journal of Jiangsu University(Natural Science Edition), 2020, 41(3): 339-345.

DOI：10.3969/j.issn.1671-7775.2020.03.015

• Image processing
• machine
• Maximum inter-class variance algorithm
• Phyllotreta striolata fabricius
• Support vector
• Yellow sticky trap

To grasp the occurrence of phyllotreta striolatas fabricius with serious damage to vegetable growth and the damage extent, a method for identifying and counting phyllotreta striolatas fabricius was proposed based on yellow sticky traps. The maximum inter-class variance algorithm(OTSU) algorithm was used to segment yellow sticky traps from the background images. OTSU algorithm, color smooth and active contour model were applied to segment phyllotreta striolatas fabricius from yellow sticky traps. Color feature, textural feature and shape feature of candidate areas were subsequently extracted, and support vector machine was built to identify and count the phyllotreta striolatas fabricius. The results show that the proposed method can achieve high accuracy of 88.16%, precision of 92.00% and recall of 81.56%, and the information of phyllotreta striolata fabricius can be obtained in real-time.

• 出版日期2020
• 单位华南农业大学