Self-similarity measurement using percentage of angle similarity on correlations of face objects Darun Kesrarat Paitoon Porntrakoon 2016-06-14T09:20:04Z 2016-06-14T09:20:04Z 2009-07
dc.description.abstract A 2D face image can be used to search the self-similar images in the criminal database. This self-similar search can assist the human user to make the final decision among the retrieved images. In previous self-similar search, a 2D face image comprises of objects and object correlations. The attribute values of objects and their correlations are measured and stored in the face image database. The similarity percentage is specified to retrieve the self-similar images from the database. The problem of previous self-similar search is that the percentage of the angle differentiation among the objects in different part is different although their angle differentiation is exactly the same. The proposed model is introduced to improve the stability of the similarity percentage by reducing the number of face objects, object correlations, and the degree calculation. After testing over 100 samples, the proposed method illustrated that the stability of similarity percentage is improved especially for the left side objects of the face image. en_US
dc.format.extent 5 pages en_US
dc.format.mimetype application/pdf en_US
dc.identifier.citation Proceedings of the 6 th International Conference on Informatics in Control, Automation and Robotics (ICINCO 2009) Vol. 2, (July 2-5, 2009), 369-373 en_US
dc.language.iso eng en_US
dc.subject Self-similarity en_US
dc.subject Face objects en_US
dc.subject Correlations en_US
dc.title Self-similarity measurement using percentage of angle similarity on correlations of face objects en_US
dc.type Text en_US
mods.genre Proceeding Paper en_US
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