Recently, there has been continuous research in fashion design using artificial intelligence. Among them, fashion designs using generation algorithms began to appear in the mid-2000s. Among generation algorithms, Generative Adversarial Network (GAN) is a method that produces plausible samples as generation models and discriminant models competitively trained. In this paper, style transfer methods were used to create Hanbok images based on contour images of Hanbok with GAN algorithm. Style transfer is a suitable way to create hanbok with a variety of designs but no large changes of shape. In this paper, we built our own color and contour images of hanbok dataset for applying style transfer. After that, we analyzed methods and results of design using DiscoGAN, CycleGAN, and Muint, which are representative style transfer methods. As a result, all three methods learned the transformation between the color domain and the contour domain to create a new hanbok image given the contour image. In addition to the basic hanbok design, it designed creative hanbok with new patterns and color changing tie. This paper demonstrates that it is possible to design hanbok using artificial intelligence and future development possibilities.