| 摘要 |
<p>A window texture extraction process for quantifying texture features in grey-level images and combining the quantified texture features with previously derived classification results. The previously determined classification results require that all of the training data and all the target data be assigned, or be capable of being assigned to one of two classes. The result is a set of new features that can be quickly analyzed to determine such properties as class membership for identification purposes. In order to fold-in the classification results, the class membership is established in previous experiments on images which have been characterized. The previous experiments are executed through the application of a window texture extraction kernel according to the invention.</p> |
