For our present purposes, an object can be thought of as any identifiable, separate, and distinct part of the visual world. Information about visual objects is cognitively stored in a way that ties together critical features, such as oriented edges and patches of color and texture, so that they can be identified, visually tracked, and remembered. Because visual objects cognitively group visual attributes, if we can represent data values as visual features and group these features into visual objects, we will have a very powerful tool for organizing related data. The object metaphor is pervasive in the way we think about abstract data. Object-oriented programming is but one example; the body politic is another. Object-related concepts are also basic in modern systems design. A modular system is one that has easily understood and easily replaced components. Good modules are "plug-compatible" with one another; they are discrete and separate parts of a system. In short, the concept of a module has a lot in common with the perceptual and cognitive structures that define visual objects. This suggests that visual objects may be an excellent way of representing modular system components. A visual object provides a useful metaphor for encapsulation and cohesiveness, both important concepts in defining modular systems.

Two radically different theories have been proposed to explain object recognition. The first is image-based. It proposes that we recognize an object by matching the visual image with something roughly like a snapshot stored in memory. The second type of theory is structure-based.