scholarly journals Research on Interactive Visual Communication Design System Based on Dynamic Image

2022 ◽  
Vol 2146 (1) ◽  
pp. 012029
Author(s):  
Runping Lai
Keyword(s):  
Image Segmentation ◽  
Original Model ◽  
Segmentation Algorithm ◽  
Design System ◽  
Sar Image ◽  
Effect Analysis ◽  
Dynamic Image ◽  
Visual Communication Design ◽  
Communication Design ◽  
Cv Model

Abstract The SVR image marine-continental segmentation algorithm on account of ameliorated CV model can segment the marine-continental image efficiently, and compare the image results with the original model, so as to continuously iterate the effectiveness of image segmentation. On account of this, this paper first analyses the concept and main methods of SAR image marine-continental segmentation algorithm, then studies the SAR image marine-continental segmentation algorithm on account of ameliorated CV model, and finally gives the process and effect analysis of SAR image marine-continental segmentation on account of ameliorated CV model.

scholarly journals Analysis of Brand Visual Design Based on Collaborative Filtering Algorithm

2022 ◽  
Vol 2022 ◽  
pp. 1-8
Author(s):  
Gao Chaomeng ◽  
Wang Yonggang
Keyword(s):  
Collaborative Filtering ◽  
Visual Communication ◽  
Visual Design ◽  
Design System ◽  
Original Algorithm ◽  
Filtering Algorithm ◽  
Visual Communication Design ◽  
Communication Design ◽  
Collaborative Filtering Algorithm ◽  
The Impact

With the continuous development of China’s social economy, the competitiveness of brand market is gradually increasing. In order to improve their own level in brand building, major enterprises gradually explore and study visual communication design. Brand visual design has also received more and more attention. Building a complete and rich visual design system can improve the brand level and attract users to consume. Based on the abovementioned situation, this paper proposes to use collaborative filtering algorithm to analyze and study brand visual design. Firstly, a solution is proposed to solve the problem of low accuracy of general recommendation algorithm in brand goods. Collaborative filtering algorithm is used to analyze the visual communication design process of enterprise brand. Research on personalized image design according to consumers’ trust and recognition of brand design is conducted. In traditional craft brand visual design, we mainly study the impact of image design on consumer behavior. The brand loyalty model is used to predict and analyze the visual design effect. Also, the user’s evaluation coefficient is taken as the expression of brand visual design recognition. Finally, the collaborative filtering algorithm is optimized to improve the consumer similarity based on the original algorithm. The results show that the brand visual design using collaborative filtering algorithm can help enterprises obtain greater benefits in their own brand construction. It provides effective data help in the development of traditional craft brands.

Dynamic image segmentation algorithm in 3D descriptions of remote sensing images

2015 ◽  
Vol 75 (16) ◽  
pp. 9723-9743 ◽  
Author(s):  
Ching-Yi Chen ◽  
Hsuan-Ming Feng ◽  
Hua-Ching Chen ◽  
Shiang-Min Jou
Keyword(s):  
Remote Sensing ◽  
Image Segmentation ◽  
Segmentation Algorithm ◽  
Remote Sensing Images ◽  
Dynamic Image ◽  
Image Segmentation Algorithm

Segmentation of Marine Spill Oil SAR Image Based on Gabor, Krawtchouk Moments and KFCM

2013 ◽  
Vol 760-762 ◽  
pp. 1462-1466 ◽  
Author(s):  
Li Zhu ◽  
Yi Quan Wu ◽  
Jun Yin
Keyword(s):  
Image Segmentation ◽  
Texture Features ◽  
Sar Image ◽  
Segmentation Method ◽  
Threshold Method ◽  
Krawtchouk Moments ◽  
Model Method ◽  
Sar Image Segmentation ◽  
Segmentation Methods ◽  
Cv Model

To further improve the accuracy of SAR image segmentation in the marine spill oil detection, a segmentation method of marine spill oil images based on Gabor, Krawtchouk moments and KFCM is proposed in this paper. Firstly, the marine spill oil image is decomposed by Gabor transform to obtain the texture features of image. Then, the Krawtchouk moments are applied to extract the shape features of image. Finally, the image segmentation is achieved based on KFCM. A large number of experimental results show that, compared with the related segmentation methods such as Tsallis entropy threshold method,CV model method and the method based on Gabor, Krawtchouk moments and FCM, the proposed method can achieve better result.

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