DATA STRUCTURES FOR GIGABYTE SYSTEMS

 

Allen Klinger

Computer Science Department

University of California, Los Angeles

 

The paper shows how data structures concepts apply in system planning.  It surveys image, sketch, text, and speech-communication. In each area, applications using data structuring, or examples appear.

 

In image processing, enhancement, compression, transmission, and feature location are central. Graphics conveys solid information: often by shading. Speech is recognition/speaker-identification oriented.

 

Outside computing, graphics has a summary quality: instead of the actual photograph, an idea of it is conveyed. Practical image processes: e.g., image-to-image comparison, texture/feature detection,

line/edge-finding, shape-characterization, and segmentation; can be combined through data structure

methods to obtain similar qualitative information.

 

As with image processing, other procedures, such as speech-computing in restricted-domains, can employ data structures. Transform or other global-data can, through data structures, support captioning or highlight regions. Thus the key result from this approach is producing supportive, and innovative information-handling.

 

Data structuring is also the basis of visualizing multiple-measure data relationships. This paper cites data structures enabling new statistical methods, improving large-record data-handling, and resulting in greater use of visual techniques for examining numerical records.

 

(This expands on a 8 July 1994 Argonne National Laboratory presentation. The above item was prepared November  4,  1994 for submission to SPIE. A similar presentation was given at the SPIE conference, San Jose, California, January 1995.)