SEAC and the Start of Image Processing at the National Bureau of Standards

Development of New Image Processing Tools

While new applications of image processing were being developed at NBS, new tools, both physical and conceptual, were being developed. Reference (11) stated that "the best way to store a photograph is in its original form." This implied that for many photographs, a larger scanner than the first SEAC scanner would be necessary if the computer was to have access to such images. In 1964, R.T.Moore, M.C.Stark, and L.Cahn at NBS built a precision scanner that could accommodate a much larger image (25). This scanner was built around a commercial lathe body offering dimensional precision of 0.127 mm. It had sufficient accuracy that repeated scans could serve the purpose of avoiding the prohibitively large memory requirements that would be needed to store a scanned image as large as 250 mm square.

In 1957, Kirsch et.al. thought that pattern recognition could proceed monotonically forward from scanning to processing to recognition. It was many years before they understood that models of the visual world would have to exist in the computer before scanned images could be effectively used. By 1964 Kirsch showed (26) that one could summarize the information about the visual world in the form of a picture grammar. Such a grammar would precede the image scanning operation and aid in pattern recognition. Much of this work was theoretical in nature and resulted in a large literature on syntactic image processing. Only in 1978, did this understanding get reformulated elsewhere (20) in the context of architecture and applied to practical problems in representation of architectural designs.

Among the tools developed were programming languages for processing images. In (13) Moore describes a subroutine library for the SEAC, written by R. B. Thomas, that made it convenient to invoke processing operations on metallurgical photograph images. Later, K. Kloss adapted for the IBM 709 computer at NBS, a simulator written at the University of Illinois. This simulator was for the Pattern Articulation Unit of the Illiac 3 computer. It was a homogeneous processor of the kind that became common with parallel processing. Kloss embedded the program in the LISP language. NBS staff also installed the system on the ANFSQ32 computer at System Development Corp. in California and used it, again remotely on slow telephone lines. D. J. Orser, I. Rhodes, and A. H. Meininger, all of NBS, also developed a LISP based image processing system installed on the DEC-10 computer at the National Institutes of Health that was used remotely at NBS.

The most recent, powerful member of this class of LISP-based image processing languages is the MacLispix language developed by David S. Bright at NIST (27). MacLispix uses the Macintosh Common Lisp language on the Macintosh computer. This is a LISP compiler and interpreter, with the full symbol manipulation capability of LISP, in which Bright has embedded efficiently coded routines for most common image processing operations. It is available as a public domain language with extensive documentation.

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