An intelligent system for detection of nematodes in digital images

We propose an automatic technique for identification of nematodes in digital images obtained by using a microscope. The proposed methodology can be used for a more detailed analysis and will help in the development of techniques for controlling these micro-organisms mainly in application areas as agriculture. The main contribution is a computational, intelligent system, for analysis of images of these worm like animals. We also describe ways to automate or to support the detection of nematodes, through information processing techniques. The results described in this article show that we have developed an efficient hybrid system combining image processing, mathematical morphology, and neural network techniques.