Pattern Recognition for Ecological Science and Environmental Monitoring: An Initial Report

Many ecological science and environmental monitoring problems can benefit from inexpensive, automated methods of counting insect and mesofaunal populations. Existing methods for obtaining population counts require expensive and tedious manual identification by human experts. This chapter describes the development of general-purpose pattern-recognition algorithms for identification and classification of insects and mesofauna and the design and construction of mechanical devices for handling and photographing specimens. This chapter presents techniques being explored in the first two years of a four year project, along with the results obtained thus far. This project’s primary focus to date has been the classification of stonefly larvae for assessment of stream water quality. Imaging and specimen manipulation apparatus that semi-automatically provides high-resolution images of individual specimens from multiple angles has also been designed and assembled in the context of this project. An additional project target has been the development of robust classification algorithms based on interest operators, region descriptors, clustering, and 3D reconstruction to automatically classify each specimen from its images.