An active semiotic system creates implicit symbols and their alphabets from features, structural combination of features, objects and patters, creates models with explicit structures that are labeled with the implicit symbols, and derive other models in the same format via diagrammatic- and graph transformations. The active semiotic system treats vision as a part of a larger system that converts visual information into special knowledge structures that drive a vision process, resolve ambiguity and uncertainty via feedback projections, and provide image understanding that is an interpretation of visual information in terms of corresponding knowledge models. Mechanisms of image understanding, including mid- and high-level vision, are presented as methods and algorithms of the active semiotic system, where they are special kinds of diagrammatic and graph transformations. Derived structures, and not a primary view, are the subject for recognition, and such recognition is not affected by local changes and appearances of the object from a set of similar views, thereby allowing a robot or unmanned vehicle to interpret images and video similar to human beings for better situation awareness and intelligent tactical behavior in real world situations.