In this work we present a method for multiresolution texture image segmentation via supervised Bayesian classification. This method takes into account a function called classification index CI (or Indice de Classification IC$+3$/). This function measures the accuracy rate of a pixel classification after it has been classified. The CI measure is based on the location of the pixel attribute vector in the observation space relative to the classes to which it must be classified. To reduce the time used in the classification process, we propose a new method (ASH: Algorithme de Segmentation Hierarchique$+3$/) that segments hierarchically the multiresolution images.
展开▼
机译:在这项工作中,我们通过监督贝叶斯分类提出了一种多分辨率纹理图像分割的方法。此方法考虑了称为分类索引CI(或Indice de Classification IC $ + 3 $ /)的函数。此功能在分类后测量像素分类的准确率。 CI测量基于观察空间中的像素属性向量的位置相对于必须分类的类。为了减少分类过程中使用的时间,我们提出了一种新方法(ASH:alam:almorithme de seatation hierarchique $ + 3 $ /),该细分分层是多分辨率的图像。
展开▼