Modeling, Estimation, and Pattern Analysis of Random Texture on 3-D surfaces
Abstract
To recover three-dimensional structure from a shaded and textural surface image involving textures, neither the Shape-from-shading nor the Shape- from-texture analysis is enough, because both radiance and texture information coexist within the scene surface. A new 3-D texture mathematical model is developed by considering the scene image as the superposition of the smooth shaded image and a random texture image. To describe the random part, the orthographical projection is adapted to take care of the non-isotropic distribution function of the intensity due to the slant and tilt of a 3-D texture surface, and the Fractional Differencing Period (FDP) model is choosen to describe the random texture, because this model is able to simultaneously represent the courseness and the pattern of the 3-D texture surface, and enough flexible to synthesize both long-term and short-term correlation structures of random texture. For estimating the parameters, a hybrid method which uses both the least square and the maximum likelihood estimates is applied and the estimation of parameters and the synthesis are done in frequency domain. Fractal scaling parameter plays a major role for classifying and/or segmenting the different texture patterns tilted and slanted due to the 3-dimensional rotation, because of its rotational and scaling invariant properties. A new classification method and a segmentation scheme fo rthe 3-D rotated texture patterns is developed.
Document Details
- Document Type
- Technical Report
- Publication Date
- Dec 01, 1990
- Accession Number
- ADA231849
Entities
People
- R. L. Kashyap
- Yoonsik Choe
Organizations
- Purdue University