Automated Deepest Point Identification in Video Inspection Anomalies
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Solution Overview
Problem
Video inspection devices face challenges in accurately and efficiently identifying the deepest point on an anomaly's surface due to the difficulty in determining the correct placement of cursors on a two-dimensional image, leading to time-consuming and potentially inaccurate depth measurements.
Innovation Solution
A method and device that automatically identify the deepest point on a surface anomaly by determining a reference surface, a region of interest, and calculating the depth of multiple points within that region using a central processor unit, thereby reducing user intervention and improving measurement accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual cursor placement is used to determine the deepest point on an anomaly, then the user can control the measurement process, but the time required for depth measurement increases and accuracy may be compromised
Solution Approach 1:
The system automatically identifies the deepest point on the anomaly surface by processing the three-dimensional data itself, without requiring manual user intervention. The processor analyzes the depth values of multiple points and autonomously determines which point represents the deepest location, thereby eliminating the time-consuming manual cursor placement process while maintaining measurement accuracy.
Solution Approach 2:
The manual mechanical operation of moving cursors using a joystick is replaced with an automated computational system. The processor uses algorithms to analyze the three-dimensional coordinates and depth values, substituting the mechanical interaction between user and interface with an automated digital processing system that quickly and accurately identifies the deepest point.
2Ease of operation
If manual cursor placement is required to identify the deepest point, then the measurement process remains simple, but the complexity of user operation increases due to multiple cursor placements
Solution Approach 1:
The complex task of manually placing multiple cursors and calculating depth measurements is extracted and automated by the processor. The system separates the manual viewing function from the automated measurement function, allowing the user to simply observe the displayed deepest point while the processor handles the complex calculations and cursor movements automatically.
3Measurement precision
If three-dimensional data is generated from two-dimensional images, then accurate dimensional measurements can be obtained, but the difficulty of assessing contour and locating the deepest point increases
Solution Approach 1:
The system provides visual feedback by displaying the identified deepest point on the two-dimensional image display. This feedback mechanism allows the user to verify the accuracy of the automated measurement by visually confirming that the marked deepest point corresponds to the actual deepest location on the anomaly, thereby resolving the difficulty of locating and verifying the deepest point.
Data Source
AI summary
A method and device for automatically identifying the deepest point on the surface of an anomaly on a viewed object using a video inspection device. The video inspection device obtains and displays an image of the surface of the viewed object. A reference surface is determined along with a region of interest that includes a plurality of points on the surface of the anomaly. The video inspection device determines a depth for each of the plurality of points on the surface of the anomaly in the region of interest. The point on the surface of the anomaly having the greatest depth is identified as the deepest point.