| id |
acadia09_153 |
| authors |
Ostwald, Michael J.; Tucker, Chris; Chalup, Stephan |
| year |
2009 |
| title |
Line Segmentation: A Computational Technique for Architectural Image Analysis |
| doi |
https://doi.org/10.52842/conf.acadia.2009.153
|
| source |
ACADIA 09: reForm( ) - Building a Better Tomorrow [Proceedings of the 29th Annual Conference of the Association for Computer Aided Design in Architecture (ACADIA) ISBN 978-0-9842705-0-7] Chicago (Illinois) 22-25 October, 2009), pp. 153-158 |
| summary |
Planar methods have typically dominated the computational analysis of architectural and urban space and form. In contrast, analytical methods that consider the formal, or visual, qualities of architectural façades, or images of buildings, are not only rare, but only a few have ever been repeated and adequately tested. The present paper outlines a new method—derived from the Hough Transform algorithm—for the dissolution of architectural images into segmented lines that can be counted and charted, and that can have their spatial orientation determined. This method for investigating the visual qualities of buildings is demonstrated in an analysis of a series of images of suburban houses. The proposed method, line segmentation, is potentially significant because it is a method not commonly used for the quantitative analysis of the formal and textural character of real buildings, it is repeatable, and it delivers consistent results if a simple procedure is followed. |
| keywords |
optical analysis, complexity, design assesment |
| series |
ACADIA |
| type |
Normal paper |
| email |
|
| full text |
 file.pdf (157,735 bytes) |
| references |
Content-type: text/plain
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| last changed |
2022/06/07 08:00 |
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