Deep Structure of Images in Populations Via Geometric Models in Populations

We face the question of how to produce a scale space of image intensities relative to a scale space of objects or other characteristic image regions filling up the image space, when both images and objects are understood to come from a population. We argue for a schema combining a multi-scale image representation with a multi-scale representation of objects or regions. The objects or regions at one scale level are produced using soft-edged apertures, which are subdivided into sub-regions. The intensities in the regions are represented using histograms. Relevant probabilities of region shape and inter-relations between region geometry and of histograms are described, and the means is given of interrelating the intensity probabilities and geometric probabilities by producing the probabilities of intensities conditioned on geometry.

• Type: Conference
• Year: 2005
• Where: DSSCV
• Authors: Stephen M. Pizer, Ja-Yeon Jeong, Robert E. Broadhurst, Sean Ho, Joshua Stough
• Keywords: Characteristic Image Regions, Computer Vision, DSSCV 2005, Image, Scale Space