Line detection and texture analysis for automatic nematode identification.

This paper is the second in a series studying procedures for estimating and calibrating features of nematodes from digital images. Two kinds of features were analyzed for recognition: those with a directional component and those with a textural component. Features that have a directional component (lateral field and annules) were preprocessed with classic algorithms and modified by directional filters. Features having texture (esophagus and intestine) were analyzed with vectors of measures to define them and the statistical technique CART (classification and regression trees) to explain the role that each measure plays in the identification and discrimination process.