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Title: Selection of tactile textures with predetermined affective properties
Author: Elkharraz, Galal Mohamed
ISNI:       0000 0004 2717 3956
Awarding Body: University of Leeds
Current Institution: University of Leeds
Date of Award: 2011
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Product improvement by manufacturing companies is becoming more customer- oriented by taking into account human affective responses. Affective engineering, which aims at translating human feeling and demand into product design, could be applied to satisfy these feelings or requirements. One of the key aspects of human touch feeling of a product is its surface texture. Therefore, the selection of surface texture is now important in domains such as packaging, car interiors, furniture and industrial design. However, designers are finding it difficult to design surface textures that satisfy certain human touch feelings. The novelty of this research is a new method to help designers synthesize tactile textures with predefined customers' touch feeling requirements. Several experiments were conducted: extracting textural features from surfaces to investigate correlations between these features and human touch feeling; synthesising a set of tactile textures that satisfy an affective specification; identifying a manufacturing process by which the synthesised textures can be made and presented to humans; and finally, testing the manufactured textures by characterising their features, comparing them to the computer definitions, and by asking humans to rate them in a psychological experiment. The correlations between the low level computational features (calculated using different statistical techniques such as first, second, and higher order statistics and Law's energy measures) and human affective responses were found. These correlations were used to synthesize new textures corresponding to predefined human touch affective responses. The results showed that the human touch affective responses could be estimated with an acceptable range of error. The effect of small changes in the topographies of the surfaces was investigated to compare 'as designed' with 'as manufactured' surfaces. Gaussian noise was added to the original texture images used to make the surfaces. Six affective responses for each new image were estimated using multiple linear regression models. The results also showed that the pixels' value change (representing height) has a significant impact on the affective responses when the signal to noise ratio is greater than 0 dB.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available