Unlock instant, AI-driven research and patent intelligence for your innovation.

Method for recognizing local damage degree of object based on three-dimensional measurement

A technology of three-dimensional measurement and recognition method, which is applied in the field of data processing, can solve the problems of difficult volume calculation and manual operation, and achieve the effect of high consistency and avoiding errors

Pending Publication Date: 2021-05-14
ZHEJIANG ANGEL SCI & TECH CO LTD
View PDF0 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The invention provides a method for identifying the degree of local damage of objects based on three-dimensional measurement, which aims to solve the problem of volume calculation difficulties in the measurement of local damage of objects, the measurement process requires manual operation, and the problems of different measurement results obtained from multiple measurements, so as to realize local damage of objects Automation of Degree Measurements

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Method for recognizing local damage degree of object based on three-dimensional measurement
  • Method for recognizing local damage degree of object based on three-dimensional measurement
  • Method for recognizing local damage degree of object based on three-dimensional measurement

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0052] Such as figure 1 As shown, a method for identifying the local damage degree of an object based on three-dimensional measurement includes the following steps:

[0053] S110. Identifying the three-dimensional point cloud data of the target object, the target object also includes a damaged part and an intact part symmetrical to the damaged part, gridding the three-dimensional point cloud data and establishing a grid model;

[0054] S120. Extract the complete data of the damaged part and the intact part from the grid model according to the shortest curvature spline method, and respectively establish samples;

[0055] S130. Calculate the volume of the sample according to the filling method and the point cloud slicing method, and compare the volumes of the sample to obtain the local damage degree of the object.

[0056] According to Embodiment 1, when the system recognizes the three-dimensional point cloud data of the target object, it must simultaneously identify the damage...

Embodiment 2

[0058] Such as figure 2 As shown, a method for identifying the local damage degree of an object based on three-dimensional measurement includes:

[0059] S210. Using a three-dimensional measurement method to identify the image of the target object, the target object also includes a damaged part and an intact part symmetrical to the damaged part, and the image contains coded information data;

[0060] S220. Capture the encoded information data, output the captured data in spatial coordinates according to the triangulation method, and obtain three-dimensional point cloud data;

[0061] S230. Perform grid processing on the 3D point cloud data, and establish a grid model according to the grid;

[0062] S240. Extract the complete data of the damaged part and the intact part from the mesh model according to the shortest curvature spline method, and respectively establish samples;

[0063] S250. Calculate the volume of the sample according to the filling method and the point cloud...

Embodiment 3

[0066] Such as image 3 As shown, a method for identifying the local damage degree of an object based on three-dimensional measurement includes:

[0067] S310. Identify the three-dimensional point cloud data of the target object, the target object also includes a damaged part and an intact part symmetrical to the damaged part, grid the three-dimensional point cloud data and establish a grid model;

[0068] S320. Estimating the normal of the grid model, and extracting N edge feature points, where N is an integer greater than 1, using an AABB tree to calculate the upper edge point and the lower edge point among the N edge feature points , and estimate the minimum closed loop curve between the upper edge point and the lower edge point according to the Dijkstra algorithm, and project the minimum closed loop curve onto the surface of the mesh model to obtain the minimum of the damaged part and the intact part Range line, starting from the minimum range line of the damaged part and...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention discloses an object local damage degree recognition method based on three-dimensional measurement. The method comprises the following steps: recognizing three-dimensional point cloud data of a target object which further comprises a damaged part and an intact part symmetrical to the damaged part, carrying out the meshing of the three-dimensional point cloud data, and building a mesh model; respectively extracting complete data of the damaged part and the intact part from the grid model according to a shortest curvature spline method, and respectively establishing samples; and respectively calculating the volumes of the sample bodies according to a filling method and a point cloud slicing method, and comparing the volumes of the sample bodies to obtain the local damage degree of the object. Compared with the traditional means, the method is accurate and fast, and the consistency of multiple recognition results is high; meanwhile, errors caused by personal measurement are avoided, the problems that in the prior art, volume calculation is difficult, manual operation is needed in the measurement process, and different measurement results are obtained through multiple times of measurement are solved, and the method for recognizing the local damage degree of the object based on three-dimensional measurement becomes more efficient, intelligent and accurate.

Description

technical field [0001] The invention relates to the technical field of data processing, in particular to a method for identifying local damage levels of objects based on three-dimensional measurement. Background technique [0002] In forensic identification, the evaluation of auricle defect or deformity mainly focuses on the range and proportion of the area difference between the auricle and the normal auricle, and the maximum projection of the injured side and the healthy side auricle is calculated by using photography, imprinting, and drawing methods. Calculate the area, and then calculate the percentage of the defect area. However, due to the irregularity of the auricle and the individual differences in the scaphoid angle (the angle between the overall auricle and the skull), it is difficult to accurately describe the shape of the auricle. , the value of the maximum projected area of ​​the auricle calculated by different methods and different identifiers will be quite dif...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
IPC IPC(8): G06K9/00G06T7/62G06T17/20A61B5/107
CPCG06T7/62G06T17/20A61B5/107A61B5/1077G06V20/64
Inventor 陈俊尹庞宏兵段动宾王恺
Owner ZHEJIANG ANGEL SCI & TECH CO LTD
Features
  • R&D
  • Intellectual Property
  • Life Sciences
  • Materials
  • Tech Scout
Why Patsnap Eureka
  • Unparalleled Data Quality
  • Higher Quality Content
  • 60% Fewer Hallucinations
Social media
Patsnap Eureka Blog
Learn More