The paper proposes a method for classifying and fast retrieving images which uses boosting metalearning to search for the most salient image features. We use local image keypoints as image features. We construct by boosting a set fuzzy rules describing image feature parameters. The rules constitute a set of weak classifiers voting for the final image class. The method can use various image features, engineered and learned by deep learning methods. We checked the methods on some real-world images.