Searching Color Images by Emotional Concepts
Most of the content-based image retrieval systems focus on similarity- based retrieval of images by utilizing color, shape and texture features. For color-based image retrieval, the average color or color-histograms of images are widely used as feature vectors. In this paper, we propose a new searching scheme, called Fuzzy Membership Value-Indexing, to guarantee higher retrieval quality. This scheme allows us to retrieve images based on high-level emotional concepts, such as ‘cool’, ‘soft’, ‘strong,’ etc. Each image is automatically classified into predefined emotional categories, by analyzing its color values in HSI color space and assigning appropriate fuzzy membership values. Our experimental results show that the proposed technique can reflect user’s searching intention more accurately.
KeywordsColor Image Image Retrieval Fuzzy Membership Emotional Category Emotional Term
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- 1.Stricker, M., Orengo, M.: Similarity of color images. In: Proc. SPIE on Storage and Retrieval for Image and Video Databases, San Jose, USA, February, vol. 2420, pp. 381–392 (1995)Google Scholar
- 3.Rickman, R., Stonham, J.: Content-based image retrieval using color tuple histograms. In: Proc. SPIE, vol. 2670, pp. 2–7 (1996)Google Scholar
- 4.Smith, J., Chang, S.-F.: Tools and techniques for color image retrieval. In: Proc. SPIE, vol. 2670, pp. 1630–1639 (1996)Google Scholar
- 5.Niblack, W., Barber, R., et al.: The QBIC Project: Querying images by content using color, texture, and shape. In: Proc. SPIE, February 1993, pp. 173–187 (1993)Google Scholar