3D Point Cloud Shape Detection via 2D Image Analysis
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Solution Overview
Problem
Conventional shape detection methods are labor-intensive and time-consuming, especially when detecting a predetermined shape on an object, as they require either manual confirmation or heavy analysis processing, making them inefficient for quick and easy identification.
Innovation Solution
A shape detection method that involves acquiring three-dimensional point group data from an object using a sensor, displaying it as two-dimensional image data, and performing image analysis to detect a predetermined shape based on predefined conditions, such as feature point size or shape characteristics.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual confirmation of predetermined shape is performed using three-dimensional model, then detection accuracy is improved, but labor time and operator load increase
Solution Approach 1:
The patent creates a two-dimensional image copy of the three-dimensional point group data displayed on the terminal. This two-dimensional image can be easily processed by image analysis algorithms, avoiding the need for operators to manually examine complex three-dimensional models while preserving the ability to detect predetermined shapes accurately.
Solution Approach 2:
The patent replaces manual visual inspection (mechanical human operation) with automated image analysis processing. By converting the three-dimensional data into a two-dimensional image and applying image analysis, the system automatically detects predetermined shapes, eliminating operator labor while maintaining detection accuracy.
2Extent of automation
If three-dimensional model analysis is performed on terminal, then predetermined shape detection is automated, but processing load on terminal increases
Solution Approach 1:
The patent extracts only the necessary visual information from the three-dimensional point group data by generating a two-dimensional image representation. This extraction reduces the data complexity and processing requirements, allowing automated analysis to be performed with lower terminal processing load while maintaining detection capabilities.
Solution Approach 2:
The patent changes the data representation parameter from three-dimensional point group coordinates to two-dimensional image pixels. This parameter transformation simplifies the data structure and enables the use of efficient two-dimensional image analysis algorithms, reducing computational burden on the terminal.
3Loss of information
If entire shape detection is performed, then comprehensive shape information is obtained, but difficulty in finding predetermined shape increases
Solution Approach 1:
The patent creates a specialized two-dimensional image copy of the three-dimensional data that is optimized for detecting predetermined shapes. This copy maintains the essential shape information needed for detection while presenting it in a format that makes predetermined shapes easily identifiable through image analysis.
Solution Approach 2:
The patent extracts and highlights the features relevant to predetermined shape detection from the complete three-dimensional shape data. By converting to two-dimensional image data, the system extracts the essential visual characteristics needed for detection while filtering out unnecessary complexity, making predetermined shapes easier to find.
Data Source
AI summary
To easily and quickly detect a predetermined shape on an object. A shape detection method for detecting the shape of an object, the method comprising: a step of acquiring data indicating three-dimensional point group data from the object by a sensor, a step of displaying the three-dimensional point group data in a display area of a terminal, a step of acquiring the display area in which the three-dimensional point group data is displayed, as two-dimensional image data, and a step of performing image analysis on the two-dimensional image data, and detecting a predetermined shape of the object.