This thesis shows highly encouraging results as the gain of accuracy reached 18.4%
when the pairwise comparisons method was used instead of the direct method for comparing
random shapes. The thesis describes a heuristic for generating random but nice
shapes, called placated shapes. Random, but visually nice shapes, are often needed
for cognitive experiments and processes. These shapes are produced by applying the
Gaussian blur to randomly generated polygons. Afterwards, the threshold is set to
transform pixels to black and white from di erent shades of gray. This transformation
produces placated shapes for easier estimation of areas. Randomly generated
placated shapes are used to perform the Monte Carlo method to test the accuracy of
cognitive processes by using pairwise comparisons. An on-line questionnaire has been
implemented and participants were asked to estimate the areas of ve shapes using a
provided unit of measure. They were also asked to compare the shapes in pairs. Such
Monte Carlo experiment has never been conducted for 2D case. The received results
are of considerable importance.
| Identifer | oai:union.ndltd.org:LACETR/oai:collectionscanada.gc.ca:OSUL.10219/2097 |
| Date | 08 October 2013 |
| Creators | Almowanes, Abdullah |
| Publisher | Laurentian University of Sudbury |
| Source Sets | Library and Archives Canada ETDs Repository / Centre d'archives des thèses électroniques de Bibliothèque et Archives Canada |
| Language | English |
| Detected Language | English |
| Type | Thesis |
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