Impact Analysis of Informatization Means Driven by Artificial Intelligence Technology on Visual Communication

With the popularization of computer technology, the combination of artificial intelligence and image processing technology has become a research hotspot in the visual communication. Image processing technology mostly involves segmentation and detection of images. Image segmentation often focuses on extracting image contour information, while ignoring the color of the image. The calculation time for image detection is relatively long, and the calculation steps are also relatively cumbersome. In response to the above issues, a density peak clustering algorithm was proposed for image segmentation. In the phase of image detection, the region recommendation network is introduced to improve the faster region Convolutional neural network algorithm. The findings demonstrate that under 15% Gaussian noise and 10% Salt-and-pepper noise, the segmentation accuracy of the density peak clustering algorithm is 98.13% and 97.89% respectively. The accuracy, recall and F-measure of the improved fast region Convolutional neural network algorithm are 98.49%, 97.29% and 97.77% respectively. The accuracy and average time consumption in the graphics processor environment are 98.18% and 2.94ms, respectively. In conclusion, the image segmentation algorithm based on density peak clustering algorithm and the improved fast region Convolutional neural network algorithm are robust, which have good segmentation and detection effects.

@article{Ni2024,
  title     = {Impact Analysis of Informatization Means Driven by Artificial Intelligence Technology on Visual Communication},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {15},
  number    = {10},
  year      = {2024},
  publisher = {The Science and Information Organization},
  author    = {Lei Ni},
  doi       = {10.14569/IJACSA.2024.0151055},
  url       = {https://doi.org/10.14569/IJACSA.2024.0151055}
}