Experimental result of feature extraction method for digital traditional Japanese crafting system

In this paper, we show the experimental result of feature extraction method for digital traditional Japanese crafting system to provide a user with the desired presentation space. The quantitative feature values are extracted by using visual pattern image coding (VPIC). These values include the total number, the frequency, the dispersion rate and the deviation rate for different edges. The quantitative feature values for traditional Japanese crafting objects are registered in the multimedia database and the relation between Kansei words and the sensitive feature of traditional Japanese crafting objects are analyzed by using the questionnaire. Then, the sensitive features are compared with the quantitative feature values. Through the above process, we can find the relation between the design pattern components and edge types using VPIC. We extract quantitative feature value by the VPIC system and evaluate its performance by test patterns and traditional fitting objects. The experimental results show that by finding the relation between the design pattern components and the edge types using the VPIC, the KRM can be realized.