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ID 35133
file
k6232_3.pdf 53.4 MB
k6232_1.pdf 348 KB
k6232_2.pdf 161 KB
title alternative
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
creator
Guo, Xiaoying
subject
visual complexity
texture images
painting images
kansei engineering
affective engineering
image features
support vector machine
color complexity
understandability.
NDC
Information science
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.……
language
eng
nii type
Thesis or Dissertation
HU type
Doctoral Theses
DCMI type
text
format
application/pdf
text version
ETD
rights
Copyright(c) by Author
grantid
甲第6232号
degreeGrantor
広島大学(Hiroshima University)
degreename Ja
博士(工学)
degreename En
Engineering
degreelevel
doctoral
date of granted
2013-09-25
department
Graduate School of Engineering



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