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Automatic quantitative assessment method for battlement missing

A quantitative evaluation and battlement technology, applied in the field of computer vision, can solve the problems of lack of quantitative damage analysis of building components, and achieve the effects of saving manpower and material resources, low cost, and improving efficiency

Pending Publication Date: 2022-04-12
WUHAN UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] However, existing methods focus on detecting visible damage on building surfaces, such as identifying damage types and locating damaged areas, and lack quantitative damage analysis of building components such as structurally damaged roofs and walls. Useful information during the repair process

Method used

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  • Automatic quantitative assessment method for battlement missing
  • Automatic quantitative assessment method for battlement missing
  • Automatic quantitative assessment method for battlement missing

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Embodiment Construction

[0042] The invention provides an automatic quantitative evaluation method for battlement loss, which uses oblique images and the generated three-dimensional model to calculate quantitative information such as volume, and at the same time studies the characteristics of building structures, extracts hidden repetition and linear symmetry information, and reduces the volume of damaged objects by calculating A small amount, to divide the damage degree; through the symmetry of the building, locate the missing parts.

[0043] The technical solutions of the present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0044] Such as figure 1 As shown, the process of the embodiment of the present invention includes the following steps:

[0045] Step 1. Using the high-resolution oblique images collected by the UAV, the 3D model with real size and proportion is reconstructed by photogrammetry.

[0046] Step 2, use the improved Mask-R...

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Abstract

The invention relates to an automatic quantitative assessment method for battlement missing. According to the method, an inclined image and a three-dimensional model generated by the inclined image are used as data sources for cultural relic building damage evaluation, and statistical data about building damage conditions are obtained by designing damage evaluation indexes and are used for guiding subsequent cultural relic protection and repair work; by analyzing the structural characteristics of the building, missing parts in the building are automatically retrieved and positioned, and important information is provided for the subsequent actual repairing process of cultural relics. The method provided by the invention does not need a large amount of manpower and professional instruments, saves manpower and material resources, and improves the efficiency of large cultural relic building damage assessment.

Description

technical field [0001] The invention belongs to the technical field of computer vision, and in particular relates to an automatic quantitative evaluation method for lack of battlements. Background technique [0002] The automatic quantitative evaluation of the damage degree of cultural relics is of great significance in the protection and restoration of cultural relics. The traditional method requires personnel to conduct on-site investigations with the help of professional instruments, which is time-consuming and laborious, and some severely damaged cultural relics cannot even be measured. The emergence of non-contact technologies such as optical imaging, SAR, and lidar has greatly accelerated the process of damage detection of large cultural relics. Oblique images have the advantages of large coverage, low cost, and fast acquisition. They can produce real-size 3D models and provide quantitative information such as area and volume for subsequent evaluation. [0003] Howev...

Claims

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Application Information

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IPC IPC(8): G06T7/00G06T7/10G06T7/62G06T17/00
Inventor 宫一平程昫高云龙
Owner WUHAN UNIV
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