Line grouping based on uncertainty modeling of parallelism and collinearity

Peter Veelaert

doi:10.1117/12.404829

23 October 2000 Line grouping based on uncertainty modeling of parallelism and collinearity

Peter Veelaert

Proceedings Volume 4117, Vision Geometry IX; (2000) https://doi.org/10.1117/12.404829
Event: International Symposium on Optical Science and Technology, 2000, San Diego, CA, United States

Abstract

Given a set of lines, line grouping considers the problem of deciding which lines are likely to belong to the same object or to a set of similar objects, before any recognition of objects has actually taken place. Vision scientists have suggested a number of factors that may be involved in the grouping process of lines, among which proximity, parallelism and collinearity are the easiest to quantify. These properties have often been measured by empirical estimates. Previous work, however, has shown that it is also possible to follow a more systematic approach based upon the uncertainty of pixel positions. Thus we can give precise definitions regarding the parallelism, collinearity or concurrency of lines whose parameters are only known to lie within given regions in the parameter space of lines. In this work we generalize this framework and show how it can be used during an entire line grouping process.

Citation Download Citation

Peter Veelaert "Line grouping based on uncertainty modeling of parallelism and collinearity", Proc. SPIE 4117, Vision Geometry IX, (23 October 2000); https://doi.org/10.1117/12.404829

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