首页> 外文会议>International Conference on Informatics in Control, Automation and Robotics >SELF-SIMILARITY MEASURMENT USING PERCENTAGE OF ANGLE SIMILARITY ON CORRELATIONS OF FACE OBJECTS
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SELF-SIMILARITY MEASURMENT USING PERCENTAGE OF ANGLE SIMILARITY ON CORRELATIONS OF FACE OBJECTS

机译:使用角度相似性百分比对面对象相关性的自相似度测量

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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.
机译:2D面部图像可用于搜索犯罪数据库中的自相似图像。这种自相似的搜索可以帮助人类用户在检索到的图像中进行最终决定。在先前的自相似搜索中,2D面部图像包括对象和对象相关性。测量对象的属性值及其相关性并存储在面部图像数据库中。指定相似百分比以从数据库中检索自相似图像。以前的自我类似搜索的问题是,尽管它们的角度分化完全相同,但不同部分的对象之间的角度分化的百分比是不同的。引入所提出的模型以通过减少面部对象的数量,对象相关性和程度计算来提高相似性百分比的稳定性。在100多个样品进行测试之后,所提出的方法示出了相似性百分比的稳定性,特别是对于面部图像的左侧对象。

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