In this paper we describe work on the recognition by computer of objects viewed by a TV camera. We have written a program which will recognize a range of objects including a cup, a wedge, a hammer, a pencil, and a pair of spectacles. A visual image, represented by a 64.x 64 array of light levels, is first partitioned into connected regions. These regions are chosen to have welldefined edges. Having chosen the regions, the program then computes properties of and relations between regions. Properties include shape as defined by Fourier analysis of the s--tfr equation of the bounding curve. A typical relation between regions is the degree of adjacency. Finally, the program matches the actual relational structure of the regions of the picture with ideal relational structures representing various objects, using a heuristic search procedure, and selects that object whose relational structure best matches the actual picture.
[1]
Lawrence G. Roberts,et al.
Machine Perception of Three-Dimensional Solids
,
1963,
Outstanding Dissertations in the Computer Sciences.
[2]
J. Doran,et al.
Experiments with the Graph Traverser program
,
1966,
Proceedings of the Royal Society of London. Series A. Mathematical and Physical Sciences.
[3]
DONALD MICHIE,et al.
“Memo” Functions and Machine Learning
,
1968,
Nature.
[4]
Adolfo Guzmán-Arenas,et al.
Decomposition of a visual scene into three-dimensional bodies
,
1968,
AFIPS Fall Joint Computing Conference.
[5]
Claude L. Fennema,et al.
Scene Analysis Using Regions
,
1970,
Artif. Intell..
[6]
Rod M. Burstall,et al.
Programming in POP-2
,
1971
.