- Title
- Limits and errors: optimising image pre-processing standards for architectural fractal analysis
- Creator
- Ostwald, Michael J.; Vaughan, Josephine
- Relation
- Architecture Science Vol. 7, Issue 1, p. 1-19
- Publisher
- Architectural Institute of Taiwan
- Resource Type
- journal article
- Date
- 2013
- Description
- The box-counting variation of fractal analysis is the most common approach to calculating the visual complexity of buildings, cities and landscapes. This method derives a numerical value from an elevation or plan of a building or space, which reflects the amount of detail present in that image across multiple scales of observation. As a way of analysing urban plans and buildings, a range of scholars and designers have employed the box-counting method over the last eighteen years. However, despite the volume of this past research, the methodological limits - including the magnitude of potential error rates that are caused by variations in the images used - are yet to be quantified. As a consequence, often widely varying results have been produced using the same mathematical method and, ostensibly at least, the same image. In response to this situation, the present paper tests four factors that are associated with image pre-processing standards for the box-counting method and which, it has been theorised, have an impact on the results. For these four factors, multiple permutations of each of seven different test images are analysed in this paper in order to determine the limits or sensitivities associated with each factor. The results of this analysis are used to understand the impact of variations in each of these data preparation factors. Thereafter, they are used collectively to identify an optimal range of standards for the initial architectural image data.
- Subject
- fractal analysis; computational analysis; visual complexity; methodological limits
- Identifier
- http://hdl.handle.net/1959.13/1340048
- Identifier
- uon:28391
- Identifier
- ISSN:2219-1577
- Language
- eng
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