Efficient detection of pests in different types of crops continues to be on today’s standards a difficult task. In order to address this problem, the implementation of an Integrated Pest Management (IPM) system involving the detection and classification of insects (pests) is essential for intensive production systems. Traditionally, this has been done by placing hunting traps and later manually counting and identifying the insects found. This has proven to be a very time-consuming and expensive process. Here’s where it enters image processing, a method that in the last few years has demonstrated to be a feasible solution to the problem. However, most of the related works with good results mostly rely on images taken from traps placed in greenhouses making the processing a bit easier given the low insect saturation of the traps, which is related to how controlled is the environment in such places. When working with the same task in fields the degree of difficulty increases exponentially given the influence of opposite conditions to the ones mentioned before. This work describes a new approach to the task, by using color image processing with quaternions. The methods proposed here provide a way to extract edge maps from images of yellow sticky traps without losing the spectral relation of the channels composing the image. As a result, all insects in the image are correctly delineated regardless of their color, size and intensity. This allows for more accurate pest detection because it is possible to discriminate and identify different types of insects. The application of this approach was compared with other methods proposed in several papers, showing promising results with much thicker and better closed edges.

在当今的标准上，有效检测不同类型农作物中的有害生物仍然是一项艰巨的任务。为了解决此问题，对于集约化生产系统而言，实施涉及害虫（虫害）检测和分类的综合害虫管理（IPM）系统至关重要。传统上，这是通过放置狩猎陷阱并随后手动计数和识别发现的昆虫来完成的。事实证明，这是一个非常耗时且昂贵的过程。它进入图像处理的地方，在过去几年中证明了该方法是解决该问题的可行方法。但是，大多数相关的工作都取得了很好的效果，主要是依靠从放置在温室中的诱集装置上获取的图像，由于诱集装置的昆虫饱和度较低，因此处理起来会更加容易，这与这些地方的环境控制程度有关。当在领域中执行相同任务时，由于与前面提到的条件相反的条件的影响，难度会成倍增加。这项工作通过使用带有四元数的彩色图像处理，描述了一种用于该任务的新方法。本文提出的方法提供了一种从黄色粘性陷阱图像中提取边缘图的方法，而不会丢失组成图像的通道的光谱关系。因此，无论其颜色，大小和强度如何，都可以正确描绘图像中的所有昆虫。由于可以区分和识别不同类型的昆虫，因此可以更准确地检测有害生物。将该方法的应用与几篇论文中提出的其他方法进行了比较，