Geo-referencing Module for Image Feature Matching

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Solution Overview

Problem

Inaccurate geo-location data in images, often due to imprecise equipment or malfunctioning equipment, leads to incorrect identification of objects in real-world locations, causing inefficiencies and errors in tasks such as tree evaluation in tree farms, where manual intervention is cumbersome and time-consuming.

Innovation Solution

A computerized geo-referencing system that uses image segmentation techniques, graphs, and spatial matching algorithms to verify, modify, or create new geo-location data for images, improving the accuracy of longitude and latitude information by matching features between reference images and input images.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If manual intervention is used to correct geo-reference information, then accuracy of geo-location data can be improved, but time consumption and computational resources increase significantly

Engineering Contradiction:

Improvegeo-location data accuracyVSAvoidtime for manual correction

Core Design Contradiction:

Measurement precisionVSLoss of time

Solution Approach 1:

The system enables automatic self-correction of geo-reference data by comparing image-captured features with vector data features. The computer automatically identifies discrepancies and adjusts geo-location information without human intervention, resolving the contradiction between accuracy and time consumption.

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The patent replaces manual mechanical correction processes with automated computer-based image processing and spatial matching algorithms. The system uses image segmentation, feature extraction, and automated comparison to substitute human-operated correction methods, significantly reducing time while maintaining accuracy.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

2Productivity

If automated geo-referencing is implemented, then processing speed increases, but accuracy of geo-location data may deteriorate due to equipment imprecision

Engineering Contradiction:

Improveimage processing speedVSAvoidgeo-location data accuracy

Core Design Contradiction:

ProductivityVSMeasurement precision

Solution Approach 1:

The system introduces image-captured features as an intermediary between raw geo-location data and final accurate positioning. By extracting features from images (such as building corners, road intersections) and matching them with vector data, the system mediates between automated processing and accuracy requirements, correcting equipment imprecision through visual feature correspondence.

Inventive Principle:

Principle #24Intermediary (Mediator)

Solution Approach 2:

The system implements feedback by comparing automatically extracted image features with known vector data features. When discrepancies are detected between captured geo-location and vector data coordinates, the system uses the vector data as reference feedback to correct the automated measurements, ensuring accuracy while maintaining processing speed.

Inventive Principle:

Principle #23Feedback

3Measurement precision

If manual correction of geo-reference data is performed, then accuracy improves, but device complexity and operational difficulty increase

Engineering Contradiction:

Improvegeo-location data accuracyVSAvoidoperational simplicity

Core Design Contradiction:

Measurement precisionVSEase of operation

Solution Approach 1:

The system performs automatic self-correction by comparing image features with vector data without requiring user intervention. The computer autonomously identifies geo-reference discrepancies and applies corrections, eliminating the need for users to manually figure out entry points or set reference points, thus maintaining accuracy while dramatically simplifying operation.

Inventive Principle:

Principle #25Self-service

4Measurement precision

If large numbers of images are processed manually, then accuracy can be maintained, but computational resources and time consumption become problematic

Engineering Contradiction:

Improvegeo-location data accuracyVSAvoidprocessing throughput

Core Design Contradiction:

Measurement precisionVSProductivity

Solution Approach 1:

The system replaces manual correction operations with automated computer-based image processing algorithms. For each image, the system automatically extracts features, compares them with vector data, and corrects geo-location information without human intervention. This substitution enables high-volume processing while maintaining accuracy through consistent automated application of correction algorithms.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Data Source

PatentUS10896218B2Computerized geo-referencing for images

Publication Date: 2021.01.19 ORACLE INT CORP

AI summary

Systems, methods, and other embodiments associated with computerized geo-referencing of images are described. In one embodiment, a method includes extracting features from an image of a location. The method includes determining similarities between the extracted features and known features within vector data for the location. The method includes generating a data structure based upon the similarities. The method includes processing the similarities to identify a match between an extracted feature and a known feature. The method includes assigning geo-location data from the vector data for the known feature to the extracted feature. The method includes identifying a position of an object within the location using the geo-location data.