Accession Number:

ADP000123

Title:

Segmentation and Aggregation: An Approach to Figure-Ground Phenomena,

Descriptive Note:

Corporate Author:

STANFORD UNIV CA DEPT OF COMPUTER SCIENCE

Personal Author(s):

Report Date:

1982-01-01

Pagination or Media Count:

11.0

Abstract:

We describe a new approach to low-level vision in which the task of image segmentation is to distinguish meaningful relationships between image elements from a background distribution of random alignments. Unlike most previous approaches, which start from idealized models of what we wish to detect in the world, this approach is not based on prior world knowledge and uses measurements which can be computed directly from the input signal. Groupings of image elements are formed over a wide range of sizes and classes while attempting to make use of all available statistical information at each level of the grouping hierarchy, resulting in far more sensitive discrimination than is possible from just local measurements. This paper explores the range of grouping capabilities and discrimination exhibited by the human visual system and discusses the application of the meaningfulness measure to each of them. Author

Subject Categories:

Distribution Statement:

APPROVED FOR PUBLIC RELEASE