A framework for the evaluation of texture features with application to diagnostic ultrasound images

A novel framework is presented to evaluate a given set of texture features, based on the set of textures they are to characterize. The textures are sampled from real images which are to be segmented, rather than the commonly used Brodatz textures. Using robust statistics, the number of outliers produced by each feature is used to determine its effectiveness in characterizing the set of textures. This framework is applied to a set of textures sampled from a sequence of diagnostic ultrasound images of an ovary in vitro. Thirty-two spatial and frequency domain texture features are evaluated.<>