Artistic style generation by image analogy using ant algorithm based on the comprehensive area feathers

This paper presents a robust scheme for texture synthesis in the process of artistic style learning based on the comprehensive area feathers of the segmented image blobs, which speeds up the process by exploiting the ant colony algorithm for the texture blobs matching firstly. The scheme also ensures the artistic style transition by the parameter setting of different sample images weights and shortens the time cost in the style generation process, which can transit the styles of several images to the targets. The preliminary experiments illustrate the scheme's good performance. Above all, the random algorithms just like the ant colony searching algorithm can enhance the comprehensive performance of the artistic style generation system.