In order to construct a machine-vision system which is robust in the face of variations in image lighting arrangements of objects viewing parameters etc. it is helpful to model the vision problem as a state-space search problem. The state-space search procedure dynamically determines an optimal sequence of image-processing operators to classify an image or to put its parts into correspondence with a model or set of models. The optimal goal state is the one with the least information distortion. The critical problem in this approach is how to compute information distortion. Details about the design of cost functions in terms of information distortions are described. A vision system VISTAS has been constructed under the state-space search model. The principles in constructing the system are presented.
Shu-Yuen Hwang, Shu-Yuen Hwang,
"State-space search as high-level control for machine vision", Proc. SPIE 1386, Machine Vision Systems Integration in Industry, (1 March 1991); doi: 10.1117/12.25386; https://doi.org/10.1117/12.25386