Image Segmentation Overlay for Targeted Survey Scanning
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Solution Overview
Problem
Conventional surveying methods require skilled manual input to identify relevant features for measurement, leading to inefficiencies and inaccuracies due to shortcuts or time-consuming manual polygon drawing.
Innovation Solution
Integration of image segmentation models, such as trained machine learning models, to automatically segment and classify features in surveying environments, allowing users to select specific features for precise point measurements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual feature identification and polygon drawing is used, then measurement accuracy can be maintained, but productivity is reduced due to time-consuming operations
Solution Approach 1:
The system performs automatic image segmentation and feature identification without requiring manual polygon drawing by the surveyor. The measurement device autonomously processes images, identifies features, and generates measurement data, allowing the system to serve itself rather than relying on continuous manual intervention.
Solution Approach 2:
The patent replaces manual mechanical operations (hand-drawing polygons, manual feature marking) with automated image processing algorithms. The segmentation model automatically identifies and segments features in images, substituting the mechanical manual drawing process with computational image analysis.
2Productivity
If automated image segmentation is implemented, then productivity is improved, but device complexity increases due to integration of machine learning models
Solution Approach 1:
The measurement device is designed to perform multiple functions: traditional surveying measurements, image capture, automatic image segmentation, feature identification, and measurement data generation. By integrating these diverse functions into a single universal platform, the system manages complexity while enhancing productivity.
Solution Approach 2:
The patent introduces an image segmentation model as an intermediary component between image capture and measurement processing. This intermediary layer automatically processes images to identify and segment features, simplifying the overall workflow while managing system complexity through modular architecture.
3Ease of operation
If manual feature selection is used, then measurement precision can be controlled, but ease of operation is reduced due to skilled input requirements
Solution Approach 1:
The system automatically identifies and segments features without requiring skilled manual input from the surveyor. The measurement device autonomously processes images, identifies relevant features, and prepares measurement data, making the operation easier while maintaining precision through algorithmic accuracy.
Solution Approach 2:
The patent employs advanced image segmentation models with adjustable parameters to optimize feature identification accuracy. By tuning segmentation parameters and using sophisticated algorithms, the system achieves high measurement precision automatically, eliminating the need for skilled manual parameter adjustment while maintaining accuracy.
Data Source
AI summary
Measurement devices such as total stations or laser scanners equipped with camera sensors can capture an image of an environment. An image segmentation model can identify and segment environmental features in the image. The measurement device can display an overlay of the segmented features on top of the image. When a user selects a particular feature, the measurement device can perform point measurements such as scanning to measure a portion of the environment associated with the selected feature. Features in the environment not selected by the user may not be included in the point measurements.