大田害虫实时检测装置及其图像预处理技术的研究

【作者】 梁义涛；

【导师】 沈宪章；

【作者基本信息】 郑州大学 ， 控制理论与控制工程， 2004， 硕士

【摘要】 我国目前正在农业领域大力推广IPM(农业有害生物的综合治理)工程。IPM的主要目标是一方面利用各种防治方法尽可能地减少有害生物造成的损失；另一方面尽可能地减小投入环境的化学农药，最终应能保障乃至增强农业的可持续发展。由此可见，农业病虫害检测预报工作是IPM工程的重要组成部分，它也是各级植保部门的主要工作。 目前普遍采用的黑光灯诱集害虫、人工识别计数的测报方法，存在识别准确性差、效率低等严重缺陷，极大地降低了测报的准确度和时效性，不利于农田害虫的防治工作及时、有效、有针对性地展开，因此本文提出了基于图像工程和计算机视觉的图像识别技术应用于农田害虫的自动检测预报。 本文设计制作了诱捕装置，诱集农田害虫，使用摄像头摄取害虫图像，并在此基础上进行了有针对性的图像预处理技术的研究；通过对所获取目标图像形态学特征的提取和选择，提出了利用害虫形态学特征进行种类识别的观点，将压缩后特征输入神经网络分类器进行识别，给出检测结果。验证了获取目标图像的装置和应用图像处理的方法的可行性和有效性。 本文针对农业大田害虫这一研究对象，进行了以下工作： 1．诱集和传输装置设计。采用植保站常用的20W、3600A黑光灯诱集害虫，设计装置使害虫落入流动的水中，借此调整害虫的姿态和保证传输过程的均匀稳定。 2．均匀光照系统的设计。借鉴无影灯原理，采用对称光源和漫反射材料制作均匀光照室保证获取图像的光照质量。 3．图像采集接口的设计。充分利用图像卡提供的良好性能，基于OK—C30S卡的API进行二次开发，利用其回调功能实现采样和处理的并行完成。 4．对图像进行预处理。在对图像进行灰度化、二值化的基础上，利用各种优化的处理算法实现图像增强处理，消除噪声，分割出目标。 5．特征选择和提取。这是对害虫图像进行识别的关键环节，分别提取了面积、周长、复杂度、七个不变矩等十四个特征，形成原始特征空间；利用特征压缩也即特征选择和提取的方法对原始特征空间压缩进行压缩。 6．农田害虫的识别与分类。 与研制的硬件装置相配合，用Visual C++ 6.0语言和Matlab图像处理工具箱实郑州大学硕士学位论文现了上述各环节的功能。另外还在VisualC++平台上调用SQL Server实现了用户管理、数据管理、数据传送模块的开发，从而构建了一个较为完整的图像识别检测系统。 由于本人的水平有限和一些客观条件的限制，论文试验在软硬件设计上还存在很多有待改进的地方。不过本人相信图像自动识别系统具有广阔的发展前景。更多还原

【Abstract】 Nowadays, China is pushing IPM greatly in agriculture. One aim of project is to decrease the amount of lost resulted from pest by using various ways. Another is to reduce the use of pesticide in environment as possible in order to ensure and even strengthen the sustainable development of agriculture. Therefore, insect pest detection and prediction of agriculture are important part of IPM project. It is the groundwork of pest control services at all levels too.At the present time the prediction method of attracting pest with black light and recognizing and counting by man is adopted generally. There are some serious shortages such as bad recognition accuracy and low efficiency. It reduces seriously accuracy and timeliness of prediction and is disadvantage in guiding insect disease prevention. Therefore, this paper researched image recognition technology based on image processing. This technology will automatically detect and predict the amount and sort of various insect pests.We designed and made the attraction device to attract agricultural pests, obtained agricultural pests’ images with the color camera and processed images . On the basis of these, we emphasized on extracting effective features based on the theory of Mathematics morphology. Then we selected features, inputted into neural network classifier, recognition, presented detection results.For this research object, pest of the field in agriculture, the paper carry on the following work:1. To design the attraction and transit device. We attracted insect pests with black light which was used by pest control services, adjusting insect pests’ posture by running water to ensure a steady transit.2. To offer equality and invariable lamp. Using the theory of shadowless lamp, we made even illumination room guarantee illumination quality to obtain the image through adopting symmetrical light source and diffuse reflection material.3. To set image collection mode by programming based on the OK-C30S image card API. It realized parallel running of the image recognition system.4. The processing of pests’ image. In this tech-develop stage, We fulfilled images enhancement The grain-pests image is smoothed by the gray morphology, enhanced by the adaptive method. Eventually, we segmented the object images form theirbackground.5. Feature extracting and selecting. It is the crucial part of the system. What features we selected are as follow: area, perimeter, complexity, equivalent circle radius, and so on. Then, we made use of K-L translation based on the global in-class discrete matrix and the distance separable rule to realize the features’ compressing.6. Image recognition and classifier design.We implemented mentioned above functions with Visual C++6.0 language, developed software package, associated with designed hardware system.Due to my poor tech and other confining of some objective condition, there are still a lot of shortcomings in design of hardware and software. However, I firmly believe that a desirable future in this field lies open to us.更多还原