基于视觉图像识别的番茄表面农药残留量无损检测方法

为了提高对番茄表面农药残留量的准确检测能力,提出一种基于视觉图像识别的番茄表面农药残留量无损检测方法。采用激光成像技术进行番茄表面农药残留区域视觉图像采集,对采集的番茄表面图像进行农药残留量的光谱特征分析,提取番茄表面农药残留区域的边缘轮廓特征,根据特征提取结果进行番茄表面农药残留区域视觉图像重构,在重构的区域图像中采用分块匹配技术进行番茄表面农药残留量区域分割,结合自适应分块特征匹配方法实现番茄表面农药残留量检测识别。仿真结果表明,采用该方法进行番茄表面农药残留量的无损性较好,输出图像的信息饱和度较高,提高了对番茄表面农药残留量的准确检测能力,在番茄病虫害防治和农药的去除等方面具有很好的应用价值。

Nondestructive detection of pesticide residues on tomato surface based on visual image recognition

In order to improve the ability of accurate detection of pesticide residues on tomato surface, a method of nondestructive detection of pesticide residues on tomato surface based on visual image recognition was proposed. The image of pesticide residues on tomato surface was collected by laser imaging, and the spectral feature of pesticide residue was analyzed to extract the edge profile of pesticide residue area on tomato surface. Based on the feature extraction results, the region of pesticide residue on tomato surface was reconstructed by visual image reconstruction, and the partition matching technique was used to segment the region of pesticide residue on tomato surface. The detection and recognition of pesticide residues on tomato surface are realized by using adaptive block feature matching method. The simulation results show that the method has good nondestructive effect on pesticide residue on tomato surface and high information saturation of output image, which improves the ability of accurate detection of pesticide residue on tomato surface. It has good application value in tomato pest control and pesticide removal.