Abstract
A new image retrieval method by integrating color and edge features is proposed in this study. We also implement a practical interface to retrieve images from image database that are relevant to the user query. The proposed system uses auto weight regulation PCA (Principal Component Analysis) algorithm for similarity measure and image retrieval.
In our proposed system, there are three steps: features extraction, similarity measure, and image retrieval. In the first step, we extract color features and edge features of a query image and save extracted features as code word. Similarity measure is done by auto weight regulation PCA algorithm in the second step. Then retrieve the most relevant images from image database optimally by comparison the projection value in codebooks with query image. The effectiveness and practicality of the proposed method has been demonstrated by various experiments
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© 2003 Springer-Verlag Berlin Heidelberg
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Chang, W.H., Cheng, M.C. (2003). Image Retrieval by Auto Weight Regulation PCA Algorithm. In: Abraham, A., Franke, K., Köppen, M. (eds) Intelligent Systems Design and Applications. Advances in Soft Computing, vol 23. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-44999-7_37
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DOI: https://doi.org/10.1007/978-3-540-44999-7_37
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-40426-2
Online ISBN: 978-3-540-44999-7
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