<title>Information-theoretic approach to image description and interpretation</title>

Abstract

We present an information-theoretic approach to the image interpretation problems. In the context of this approach such tasks as contour extracting, constmcting the most informative image features and image matching are described as a single unified problem. Our approach is based primarily on the interpretation ofthe image (or image set) representation problem as a Minimum Description Length (MDL) problem. The image matching turns out to be a generally adopted method of images alignment by maximization of their mutual information. However, instead of using the pixels intensities themselves a more condensed data representation form can be used to reduce the dimensionality of input data and to extract the invariant information: hierarchical image structural description. Though we developed and successfully applied the informationtheoretic approach for the images matching, it can be extended to the other problems, e.g. the changes detection.

Determining the orientation of the observed object in threedimensional space using stereo vision methods

“…There are two basic approaches to the determination of the angle of observation or combination of reference and current visual information that can be divided by the fact whether there is alignment in the image plane or in three-dimensional space. In the first case, the current image should be aligned with the template image formed for the corresponding angle, distance, lighting conditions and background [1]. In this approach, the number of templates for each object can be quite large, and the process of aligning with each of them to establish the angle could become resource consuming.…”