Texture image compression method based on geometric information of three-dimensional model

Abstract

The invention provides a texture image compression method based on geometric information of a three-dimensional model in allusion to limitations of traditional product defect detection based on a machine vision method in applicable targets and a problem how a region-of-interest of the human eyes on a texture image is solved in the compression process. According to the invention, a region-of-interest of the human eyes is on a texture image is solved by using model grid data, three-dimensional feature points representing surface detail information of the three-dimensional model after multi-solution re-gridding and mapping points thereof on a texture space are extracted according to a visual presentation mode of the texture so as to act as texture feature points, class aggregation is carried out on the feature points in the image by using a K-means clustering algorithm according to the continuity of an image space, the region-of-interest of the texture image is acquired, and the differentiation precision of the region-of-interest and the background is improved. The method provided by the invention is verified through establishing an ROI based EZW coding and decoding experiment system, and good experiment effects are acquired.

Description

technical field [0001] The invention relates to the field of image processing, in particular to a texture image compression method. Background technique [0002] As the theoretical basis of computer graphics and related software and hardware technologies continue to mature, 3D modeling technology is gradually integrated into Internet applications, and has achieved important applications in web3D e-commerce, enabling users to obtain similar real-world images in the network environment. experience. However, high-precision 3D scanning and reconstruction technology not only meets the needs of users for the realism of virtual scenes and object models, but also causes a huge amount of model data and texture data. These data not only occupy a large amount of storage space, but also reduce the speed of model transmission and loading, which seriously affects the experience of network users and restricts the development of Web3D. Researchers reduce the amount of data by compressing ...

AI Technical Summary

Problems solved by technology

[0005] In order to solve the problems in the prior art, and conduct in-depth research on the limitations of the traditional machine vision-based method for product defect detection and the problem of how to obtain the area of ​​interest of the human eye on the texture image during the compression process, the present invention proposes a A texture image compression method based on the geometric information of a 3D model. This method obtains the region of interest of the texture image and improves the accuracy of distinguishing the region of interest from the background. It can use the geometric information of the grid to determine the important region of the texture image, and realize Prioritized compression and transmission of image region of interest data

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