On Wine Label Image Data Augmentation Through Viewpoint Based Transformation

With the improvement of people’s living standard and the development of red wine culture， it has become more and more important to establish an efficient automated wine label image retrieval system. However， the classes of wine label images are unbalanced and some classes are a few number of images so that the wine label image retrieval model based on deep learning is difficult to train. Therefore， data augmentation for wine label image becomes more necessary and urgent. In order to solve this problem， we propose a specialized data augmentation algorithm for wine label image. Specifically， we consider the wine label on the wine bottle as a cylinder and project it on the plane being tangent with the cylinder from a viewpoint to form the wine label image. In this way， we can make the cylinder modeling or reconstruction from a wine label image， and move the viewpoint up and down， left and right， far and near， to generate a new projection wine label image from the cylinder wine label with the viewpoint transformation. Experimental results on a large-scale wine label image dataset show that this viewpoint transformation-based data augmentation strategy can effectively increase the number of essentially different images of the same wine label， and significantly improve the retrieval ability of the wine label retrieval model.