An Eye for Aphids
In mid-February 2006, Martin DuSaire of the USDA contacted the IMA asking for help in using new imaging techniques to obtain accurate counts of aphids on soybean leaves. Long-term visitor Chang-Ock Lee (KAIST) and his graduate student Jooyoung Hahn responded to the challenge by optimizing their segmentation algorithm, which utilizes geometric attraction-driven flow and edge regions, for soybean leaf images. The method involves a geometric analysis of eigenspace in a tensor field on a color image as a two-dimensional manifold and a statistical identification of edge-regions; it requires neither interaction with end users nor mid-process parameter manipulations. Within a few weeks, Lee and Hahn were providing highly accurate, efficient aphid counts.
- IMA Preprint #2125: Highly accurate segmentation using geometric attraction-driven flow in edge-regions,Jooyoung Hahn and Chang-Ock Lee