Emotion-based Textile Indexing usinig Neural Networks

This paper proposes a neural network based approach for emotion-based textile indexing. Generally, the human emotion can be affected by some physical features such as color, texture, pattern, and so on. In the previous work, we investigated the correlation between the human emotion and color or texture. Here, we aim at investigating the correlation between the emotion and pattern, and developing the textile indexing system using the pattern information. Therefore, the survey is first conducted to investigate the correlation between the emotion and the pattern. The result shows that a human emotion is deeply affected by the certain pattern. Based on that result, an automatic indexing system is developed. The proposed system is composed of feature extraction and classification. To describe the pattern information in the textiles, the wavelet transform is used. And the neural network is used as the classifier. To assess the validity of the proposed method, it was applied to recognize the human emotions in 100 textiles, and then our system produced the accuracy of 90%. This result confirmed that our system has the potential to be applied for various applications such as textile industry and e-business.