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In this paper, we first studied the action recognition method based on image texture features, established a human body model, and realized the extraction of skeletal data and joint calibration. Based on the skeleton information, the aerobic movements are recognized, the difference between the aerobics movement sequence and the standard movement sequence is calculated, and the movements are scored. Then, the database for aerobic movements was established, and an AI-assistant aerobics teaching model was developed. Finally, the effect of the teaching method was analyzed through indicators of recognition effect, skill impact, and students’ learning interests. The results show that the accuracy of the system’s action recognition reaches 95%, and the overall response time is between 5.2-6.4s, with high real-time performance. And it has a significant effect on students’ movement participation, active interest, and independent learning behavior, with p-values of 0.013, 0.041, and 0.036, respectively, p

In this paper, the importance of modern packaging design and pattern design and the application of pattern design in modern packaging design are the first two aspects of achieving the development of information integration of packaging design and pattern design, and the visual design based on Markov random field is proposed for the image retrieval and classification problems in traditional model packaging design and pattern design. Wavelet transforms, multi-scale analysis of image texture features and region merging conditions in visual design using GBIS algorithm, and image retrieval in pattern design are examined and analyzed. The results show that the model trained with both loss functions has the best retrieval top-k accuracy on both datasets, reaching 54.3% on the DARN dataset and 3.9% accuracy on Deep Fashion. This paper demonstrates the model’s effectiveness for modifying and retrieving pattern design image attributes.

In this paper, we propose an adaptive gamma transform that adjusts the local values of bright and dark parts to enhance the effect of low-illumination images, thereby improving the light component. We then apply diff texture enhancement to enhance the contrast of images processed by the Retinex algorithm, thereby optimizing the perception of overexposed and underexposed imagery. Analyze the effect of image brightness enhancement based on a nonlinear transformation combined with the LOL dataset. Use PSNR and SSIM image quality evaluation criteria to analyze the visual effect of improving low-illumination images based on Retinex theory. Create a dataset of power marketing field operation inspection images and examine the effects of overexposure and underexposure image processing on four types of images: high-voltage towers, transmission lines, high-voltage fixtures, and high-voltage wireframes, using the low-light image texture fusion algorithm based on Retinex theory. Overall, this paper’s algorithm and the three DeblurGAN and DMCNN models achieve the effect of deblurring overexposed and underexposed power marketing field operation inspection images. From the local details, the model in this paper has a better effect on the de-exposure of the image, which can provide effective help for the electric power staff to understand the situation of the electric power marketing operation site and has strong practicality.

With the rapid development of modern industry and science and technology, in recent years the fault diagnosis method based on image processing has become a research hotspot in the field of mechanical fault diagnosis. In this paper, image characteristics are extracted from multiple aspects such as image texture, color, shape, etc. A grayscale symbiotic matrix image feature extraction method is proposed. On this basis, the algorithm for extracting gray symbiotic matrix time-frequency image features is designed. At the same time, the algorithm and parameters of mechanical structure identification are optimized to identify and diagnose mechanical faults. The results show that the grayscale symbiotic matrix time-frequency image feature extraction algorithm is able to accurately diagnose the wear-type faults, overwork-type faults, and short-circuit-type fault behavior of the mechanical equipment. All of them are able to obtain more than 80% accuracy, and all of them are able to reach 99.99% accurate detection of mechanical faults, which proves the effectiveness of the method of this research.

In this paper, the color image is converted to a grayscale image in the image recognition preprocessing stage to accelerate the image recognition processing, and then the image contrast is enhanced by grayscale stretching to compute the grayscale layer covariance matrix and image texture features. Multi-step Markov clustering method is proposed to optimize the GCN, and the instance normalization layer and batch normalization layer are added to strengthen the source domain representation ability of the GCN to form a cross-domain image recognition algorithm based on a pairwise generalization network. Elaborate the visual design path of image information by artificial intelligence image recognition and image processing technology, introduce image recognition technology into the field of visual design, establish a visual design partition model, and completely extract the local feature information of computer image graphics. Use the dataset to evaluate the performance of pairwise generalization networks, and conduct simulation experiments to analyze the visual expression effects of visual design. The PGN-RM method, with the addition of maximum mean distance, instance normalization, and batch normalization, is able to achieve a performance average of 91.843. The peak signal-to-noise ratio of the actual effect image of the visual design of the product packaging is maintained in the range of [95.0312, 97.0032], which is an excellent visual design effect. Visual design that utilizes artificial intelligence graphic recognition technology can express design ideas more deeply and enhance the visual design’s attractiveness.

This paper establishes different detail-level terrain grids for different terrain data blocks and generates multi-resolution terrain based on the tree-structured LOD model as a way of layering large-scale terrain data. Then, the virtual environment’s visual and image texture are rendered to visualize the virtual spatial environment. Then, the overall architecture of the interaction platform was designed, and the virtual space design visualization and interaction effects were studied based on spatial distance perception, presence experience perception, and error analysis. The results show that there is a significant difference between the mean value of people’s perceived satisfaction in the interaction space and non-interaction space M=163.138, t=1.376, p=0.005

Visual communication design and printmaking art are two independent art disciplines, but they have many similarities in graphic design, color matching and other aspects. This paper demonstrates the extraction of printmaking features using the improved LBP algorithm. The method of color histogram and color space is used to complete the color extraction of the image, and the texture features of the image are described by combining signal processing and statistical analysis. The LBP algorithm is used to locate the center pixel of the image to form a binary bit string, and the pattern value is obtained by multiplying each binary bit by the corresponding weight and summing up. The efficiency of image texture acquisition is enhanced by adding neighborhood gradient multiscale to the LBP algorithm. To obtain printmaking art elements and propose a direction for integration with visual communication design, image feature extraction is applied to printmaking art element extraction. The performance of texture classification for images has been significantly improved by the improved LBP algorithm, as shown in the results. On the Outextc10 texture dataset, DLBP5 achieves the highest classification accuracy of 92.19% by extracting colors, textures and shapes in printmaking and applying the features with elements of printmaking to visual communication design. Under the direction of integrating printmaking art style elements with visual communication design, users selected {unique, packaging design}, {vivid, branding design}, and {sharp, advertisement design} with higher satisfaction gradients, with ratings of 4.62, 4.17, and 4.36, respectively, which are all greater than 4.