System Design and Realization of Computer Image Processing Technology in Comic Creation

As an important branch of computer technology, computer graphics and image processing technology has been widely used in visual communication systems. Works designed with graphics and image processing technology have a strong impact on people’s vision. The birth of this technology has enriched creators’ creative means and improved innovation. Through the research on the related content of computer graphics and image processing technology, and make the designer’s work more perfect.

GAN Image Generation and Detection Technology Based on Fractal Dimension

With the development of modern technology today, image analysis technology has become an important research direction in the computer field. Computer image processing technology is a cross and fusion involving multiple disciplines, which includes multiple research directions such as physics, chemistry, and computer science. Starting from the fractal dimension, this article studies the image generation and detection technology. The purpose of the research topic in this article is to have a deep understanding of image generation technology so as to master image processing methods proficiently. The methods used in this article include case analysis, data, comparison, and experimental methods, etc., and carry out related researches on image generation detection technology and fractal dimension. The experimental results show that the algorithm accuracy of GAN in the detection technology of computer-generated images is higher than other algorithms, and the improvement space is about 0.06.

The System Research and Implementation for Autorecognition of the Ship Draft via the UAV

The reading of the ship draft is an important step in the process of weighing and pricing. The traditional detection method is time-consuming and labor-consuming, and it is easy to lead to misdetection. In order to solve the above problems, this paper introduces the computer image processing technology based on deep learning, and the specific process is divided into three steps: first, the video sampling is carried out by the UAV to obtain a large number of pictures of the ship draft reading face, and the images are preprocessed; then, the deep learning target detection algorithm of improved YOLOv3 is used to process the images to predict the position of the waterline and identify the draft characters; finally, the prediction results are analyzed and processed to obtain the final reading results. The experimental results show that the ship draft reading method proposed in this paper has obvious effects. The method has a good detection effect on high-quality images, and the accuracy rate can reach 98%. The accuracy rate can also reach 73% for the images with poor quality caused by improper capture, character corrosion, bad weather, etc. This method is a kind of artificial intelligence method with safe measurement process, high measurement effect, and accuracy, providing a new idea for related research.