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Color pattern selection using linguistic image scales

In this paper, we propose a novel scheme to construct the color pattern retrieval system, which can recommend color patterns of the desired human feeling. The desired feeling is represented as a 9D vector in linguistic image scales. That means a component value of the vector is the degree of the feeling in the corresponding linguistic image scale. Then the system recommends color patterns of desired feeling after it compares the given query vector with emotional features of stored color patterns. In order to construct the system, the emotional features are taken from outputs of the neural network which has inputs as the physical features extracted from color patterns. To make indexing system, the hierarchical clustering method with fuzzy c-mean algorithm is used. To verify our scheme, a set of 368 color images for textile design is selected and experimented. Using the proposed retrieval scheme, we could obtain a promising results even though several problems are still remained. We believe this pilot system can be improved to find corresponding textile designs, wall papers, or pictures in a gallery for linguistic queries of human feelings.