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Proceedings Paper

Functional programming for computer vision
Author(s): Thomas M. Breuel
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Paper Abstract

Functional programming is a style of programming that avoids the use of side effects (like assignment) and uses functions as first class data objects. Compared with imperative programs, functional programs can be parallelized better, and provide better encapsulation, type checking, and abstractions. This is important for building and integrating large vision software systems. In the past, efficiency has been an obstacle to the application of functional programming techniques in computationally intensive areas such as computer vision. We discuss and evaluate several 'functional' data structures for representing efficiently data structures and objects common in computer vision. In particular, we will address: automatic storage allocation and reclamation issues; abstraction of control structures; efficient sequential update of large data structures; representing images as functions; and object-oriented programming. Our experience suggests that functional techniques are feasible for high- performance vision systems, and that a functional approach simplifies the implementation and integration of vision systems greatly. Examples in C++ and SML are given.

Paper Details

Date Published: 30 April 1992
PDF: 12 pages
Proc. SPIE 1659, Image Processing and Interchange: Implementation and Systems, (30 April 1992); doi: 10.1117/12.58409
Show Author Affiliations
Thomas M. Breuel, AI Lab./MIT (United States)


Published in SPIE Proceedings Vol. 1659:
Image Processing and Interchange: Implementation and Systems
Ronald B. Arps; William K. Pratt, Editor(s)

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