Mathematical morphology, granulometries, and texture perception

In this work we present a classical morphological tool, granulometry, and a practical application on medical images, pneumoconiosis classification. The radiologist diagnose on these images is based on a preattentive discrimination process of the textural patterns appearing at the pulmonar parenchyma. Thus, in order to automatize this classification we have chosen a tool which agrees with perceptual theories of Computer Vision on texture discrimination. Our work is centered, concretely, on the perceptual models based on texton theory. These works base texture discrimination on differences in density of texton attributes. We link this approach with a morphological tool, granulometry, as a helpful multi-scale analysis of image particles. The granulometric measure provides a density function of a given feature, which depends on the family of algebraic openings selected. Thus in this paper we defined different granulometries which allow us to measure the main texton features, such as, shape, size, orientation or contrast, proposing a granulometric analysis as a systematic tool for texture discrimination according to a perceptual theory. And finally, we present the application of measuring size density on some radiographic images suffering from pneumoconiosis.