英文摘要 |
With the great advancement of computer hardware,artificial intelligence can be applied in various fieldswhich include image design.The introduction of imagestyle transferring has become one of the important themesin the field of artificial intelligence research. Using ANN(Artificial Neural Network) to produce images of styletransferring is better than similar applications in otherfields. However, in printing industry, images are printedon different materials, such as glass, textile, plastic, etc.If the resolution of images is not sufficient, the imageswill be blurred on products. In this study, the decreaseof resolution after style transferring method is focused.So as to solve the problem, real-time super-resolutionmethods, such as feature reconstruction loss and stylereconstruction loss, are applied to adjust the resolution ofthe images, so that the resolution of the style transferringimages is as close to that of the original images aspossible, and preserve the style texture and color. Inaddition, with the automatic mask generation technology,the technology is applied to judge the darker colors in theoriginal images and to replace them with black, the lighterones with white, and the intermediate ones with gray,and will then generate masks that can be applied to theimage processing of printing, to produce printing stacks,and to print translucent or opaque effects. The final goalis to achieve high resolution image quality for printing ondifferent materials after style transferring. |