Airport Mapping Database Change Detection Using Image Invariant Moments
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Solution Overview
Problem
The current manual process of updating airport mapping databases with new features from satellite imagery is highly human-intensive, time-consuming, and costly, with a risk of missing difficult-to-detect features.
Innovation Solution
A method and system that automatically compare aerial or satellite images by analyzing image invariant moments to identify feature changes, using feature vector data to generate templates and detect changes between new and old images, reducing the need for manual analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual visual comparison by analysts is used to detect feature changes, then detection accuracy can be maintained through human expertise, but the process becomes extremely time-consuming and costly
Solution Approach 1:
The patent replaces the mechanical visual inspection process performed by human analysts with an automated computer-based system that uses image processing algorithms. The system automatically compares new satellite imagery with existing database features using techniques such as template matching, feature extraction, and change detection algorithms, eliminating the need for manual visual comparison while maintaining detection accuracy.
Solution Approach 2:
The patent introduces an automated image processing system as an intermediary between the satellite imagery and the final change detection results. This intermediary system performs preliminary analysis, feature extraction, and comparison tasks, reducing the workload on human analysts and significantly accelerating the update process while maintaining or improving detection accuracy.
2Reliability
If manual analysis is performed to ensure accurate feature detection, then difficult-to-detect features may be identified through expert judgment, but the process requires extensive human resources and increases costs
Solution Approach 1:
The patent replaces complex manual analysis processes with automated computational algorithms that can systematically evaluate all features in the imagery. The system uses multiple detection methods including template matching, edge detection, and pattern recognition algorithms that can identify difficult-to-detect features consistently without human fatigue or subjectivity.
Solution Approach 2:
The patent implements feedback mechanisms where the automated system's detection results are validated and refined through iterative processing. The system can adjust its detection parameters based on feedback from previous analyses, improving its ability to reliably detect difficult features while maintaining automated operation and reducing the need for complex manual intervention.
3Productivity
If automated methods are used to speed up the update process, then processing time is reduced, but the complexity of the system increases
Solution Approach 1:
The patent employs automated image processing systems with algorithms for feature extraction, template matching, and change detection. These computational methods automatically analyze satellite imagery and compare it with existing database features, achieving rapid processing speeds while the system complexity is managed through standardized software architectures and established image processing techniques.
Data Source
AI summary
A method for automatically updating a graphical information system (GIS) type database using aerial imagery. The method may involve processing a new image to identify at least one target region therewithin; analyzing the target region to determine image invariant moments thereof; using feature vector data to generate a template of a target feature from an old image; analyzing the template to generate image invariant moments thereof; and comparing the image invariant moments of the target region with the image invariant moments of the template to identify a feature change between the target region and the template.