Fuzzy Similarity-Based Emotional Classification of Color Images

This paper proposes a novel scheme for evaluating an emotional response to color images. The proposed scheme uses case-based reasoning in which the prototypical color images for each emotion are stored as cases and are compared with the images to be evaluated. In the comparison, the similarities in...

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Bibliographic Details
Published in:IEEE transactions on multimedia Vol. 13; no. 5; pp. 1031 - 1039
Main Authors: Lee, Joonwhoan, Park, EunJong
Format: Journal Article
Language:English
Published: New York, NY IEEE 01.10.2011
Institute of Electrical and Electronics Engineers
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
Analogies
Applied sciences
Approximation methods
Artificial intelligence
Case-based reasoning
Classification
Color
Computer science; control theory; systems
emotional evaluation of color images
Emotions
Exact sciences and technology
Fuzzy
fuzzy similarity relation
Human subjects
Image color analysis
inter-and intra-similarities
Mathematical analysis
MPEG-7 visual descriptors
Pattern recognition. Digital image processing. Computational geometry
rough approximation
Studies
Texture
Training
Transform coding
Visualization
Weight measurement
Computer vision
Similarity
Image processing
Case-based reasoning
fuzzy similarity relation
Emotion emotionality
Case based reasoning
Texture
Color image
emotional evaluation of color images
Case study
Fuzzy logic
Rough set theory
Multidimensional analysis
rough approximation
MPEG-7 visual descriptors
Metric
inter-and intra-similarities
Image classification
ISSN:1520-9210, 1941-0077
Online Access:Get full text
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Summary:This paper proposes a novel scheme for evaluating an emotional response to color images. The proposed scheme uses case-based reasoning in which the prototypical color images for each emotion are stored as cases and are compared with the images to be evaluated. In the comparison, the similarities in terms of image descriptors play an important role, and their combination is crucial for the construction of a proper similarity measure. In the training phase of the proposed scheme, the weights that represent the unequal importance of each descriptor is determined in order to obtain a similarity measure that can be used to evaluate and classify a color image with respect to a pair of emotions. Prior to classification, the representative color images are chosen for each emotion by human subjects and are stored as cases. The stored images are compared with an image to be classified using the constructed similarity measure to determine which emotion is appropriate between a pair of emotions. In this study, we used color and texture descriptors recommended by MPEG-7, represented as high-dimensional vectors. In the training, we proposed a method based on the rough approximation and the fuzzy inter- and intra-similarities to determine the weights that represent the unequal importance of the complex MPEG-7 descriptors. Experimental results show a promising performance for the proposed scheme, and better performance could be achieved by including more prototypical images as cases.
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ISSN:1520-9210
1941-0077
DOI:10.1109/TMM.2011.2158530