A Method for Seamless Texture Mapping of 3D Models Based on Histogram Matching

Abstract

The invention provides a method for texture mapping in the process of building a three-dimensional model. By obtaining the original image and its coordinates corresponding to the triangular surface grid data; the visibility analysis of the triangular surface of the reconstructed model; Optimizing the reference image and the neighborhood topological relationship of the triangular faces, clustering the triangular faces into several reference texture patches; automatically sorting the texture patches to generate texture images; taking the histogram of the texture patch of a triangular face as a benchmark, comparing For the texture patch adjacent to the triangular surface, perform histogram matching, and change the pixel gray value of the texture patch of the adjacent triangular surface; perform step 5 on the texture patch of all triangular surfaces and the texture patch of its adjacent triangular surface; Weighted fusion of pixels to generate the entire texture image. For the first time, it is proposed to improve the texture accuracy and reduce the calculation time through the histogram matching method for the surrounding acquisition scheme of the target with limited volume.

Description

technical field [0001] The invention relates to the technical field of shape measurement, in particular to the technical field of 3D shape measurement. Background technique [0002] When performing 3D measurement, using 3D measurement data for processing and manufacturing, or using 3D data for display and identification, a relatively accurate 3D model should first be established for the target object. The currently commonly used methods include using machine vision to collect pictures of objects from different angles, and matching and splicing these pictures to form a 3D model. These 3D models can be regarded as the digitization of real things, and these data can be used to process and manufacture matching objects that match the target. For example, 3D data of human feet can be collected to make more suitable shoes. In addition, these data can also be used for identity verification. For example, after synthesizing the 3D model of the human iris, it can be used as identity...

AI Technical Summary

Problems solved by technology

However, in practical applications, it is found that unless there is an accurate angle measurement device, the user is not sensitive to the angle, and it is difficult to determine the angle accurately; the size of the target object is difficult to accurately determine, especially in some applications where the target object needs to be replaced frequently. A lot of extra work is required, and professional equipment is required to accurately measure irregular targets

Measurement errors lead to camera position setting errors, which will affect the speed and effect of acquisition and synthesis; the accuracy and speed need to be further improved

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