Modeling the Perception of Visual Complexity in Texture Images and Painting Images
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| Title ( eng ) |
Modeling the Perception of Visual Complexity in Texture Images and Painting Images
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| Title ( jpn ) |
テクスチャー画像および絵画に対する複雑さの知覚モデルの構築
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| Creator |
Guo Xiaoying
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| Abstract |
This thesis devotes to building a relationship between human visual complexity perception and objective image features.
Visual complexity of images is a worth-well investigation. It has a wide range of applications from computer science (emotion semantic image retrieval, digital watermarking and image analysis, etc.) to arts (the design of product surface, wallpapers, painting appreciation and selection, etc.). Various methods for computing image complexity have been developed depending on different applications, such as information theory, fractal dimension, quad tree method, etc. However, these measures are not sufficiently related to human visual perception of complexity. Intuitively, visual complexity is influenced by various factors perceived by humans from the image, not directly related to simple objective measures like distribution of spatial frequencies.…… |
| Keywords |
visual complexity
texture images
painting images
kansei engineering
affective engineering
image features
support vector machine
color complexity
understandability.
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| NDC |
Information science [ 007 ]
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| Language |
eng
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| Resource Type | doctoral thesis |
| Rights |
Copyright(c) by Author
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| Publish Type | Not Applicable (or Unknown) |
| Access Rights | open access |
| Dissertation Number | 甲第6232号 |
| Degree Name | |
| Date of Granted | 2013-09-25 |
| Degree Grantors |
広島大学
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