纹理图像特征化的置信决策支持与拒绝
Belief decision support and reject for textured images characterization
摘要：
纹理图像的分类假设是将具有相同纹理的图像按照区域进行分类。在不确定的环境中，它可以更好地采取不精确的决策或拒绝对应于一个unlearning类的区域。此外，在作为分类单元的区域上，我们可以有多个纹理。这些考虑使我们能够开发一个信念决策模型，允许拒绝一个区域作为unlearning，并决定工会和交叉点的学习类。所提出的方法发现其所有的理由在应用程序中的海底特性从声纳图像，这有助于说明。
英文摘要：
The textured images' classification assumes to consider the images in terms of area with the same texture. In uncertain environment, it could be better to take an imprecise decision or to reject the area corresponding to an unlearning class. Moreover, on the areas that are the classification units, we can have more than one texture. These considerations allows us to develop a belief decision model permitting to reject an area as unlearning and to decide on unions and intersections of learning classes. The proposed approach finds all its justification in an application of seabed characterization from sonar images, which contributes to an illustration.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
