A Cavity Depth and Volume Estimation Technique to Support Data Collection in an Image Mining Oriented Geoprocessing System

摘要

Spatially defined information is essential to support decision making in several areas, such as in therapeutic procedures to reduce or healing lesions in human body. So localization together with images and many other data can constitute a database to feed an Image Mining oriented Geoprocessing. Besides that low cost additional infrastructures are attractive to install large-scale use of image capturing and interpretation for health assistance. In such context geometric features of cavities can be remotely captured to monitor patients with wounds called pressure ulcers (PU). An image with linear shadows on the cavity of a model is generated in order to enable the measurement of its deformation caused by depth. This yields maximum depth and vol-ume in an experimental model that are compared with measurements made previously in a conventional manner. Partially satisfactory results suggest improvements in image capturing device and computational pro-cedures.