Fragment reconstruction method based on local texture pattern

Abstract

The invention discloses a fragment reconstruction method based on a local texture pattern and belongs to the technical field of digital image processing. The method aims to provide a local two-value mode with a normal direction based on the local texture features of fragments, so as to splice fragments of documents (orimages) broken or messed up due to natural or human factors, so that the original information can be restored in the maximum degree. First, image pre-treatment is performed on the fragments. Then, an ND_LBP unit is calculated and a weight column diagram of the ND_LBP is obtained. Finally, fragment reconstruction is implemented according to a matching relation judged through the weight column diagram of the ND_LBP. The method has characteristics of small computation volume, high anti-noise capability and high resolution.

Description

technical field [0001] The invention relates to a fragment reconstruction method based on a local texture mode, and belongs to the technical field of digital image processing. Background technique [0002] The problem of splicing fragments is a challenge encountered in many research fields, for example: damaged ancient calligraphy and painting classics need to be repaired by archaeologists, messy documents and photo fragments and other physical evidence need to be combined and restored by public security organs, and precious works of art are damaged. Afterwards, artists are required to repair and imitate. When the number of fragments is small, it can be spliced ​​by hand, but in the face of a large number of fragments, especially when irrelevant fragments may be mixed, manual splicing is an extremely heavy physical and mental work. At the beginning of the birth of computer vision technology, experts in related fields hoped to use the large-scale information processing capab...

AI Technical Summary

Problems solved by technology

[0002] The problem of splicing fragments is a challenge encountered in many research fields, for example: damaged ancient calligraphy and painting classics need to be repaired by archaeologists, messy documents and photo fragments and other physical evidence need to be combined and restored by public security organs, and precious works of art are damaged. Afterwards, artists need to repair the imitation

The challenge of matching based on edge information is that when facing fragments with similar edge shapes or missing edge parts, the matching accuracy is very low

In the actual situation, there are indeed such problems: First, when people shred a piece of paper, they often fold and tear it repeatedly, and many pieces with similar shapes will be torn out; this is especially true for documents shredded by a shredder. almost identical

This method takes into account the global nature of fragments, but the problem is: first of all, the content of many images and documents cannot be obtained in advance

[0009] This kind of LBP does not have rotation invariance. When the image is rotated, the LBP value also changes.

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