Invariant Component Detection for Navigation Database Features
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Solution Overview
Problem
Collecting and identifying geographic features such as road signs and markings for navigation systems is a time-consuming and intricate process, requiring efficient methods to detect and associate data for effective navigation.
Innovation Solution
A method involving the collection of images along paths, where invariant components are determined and compared to reference components in a data library, allowing for the identification of path markings and enhancement of navigation databases.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional methods are used to collect and identify geographic features, then detection accuracy can be maintained, but the process is time-consuming and inefficient
Solution Approach 1:
The patent extracts invariant components from images and creates a data library of reference components. By comparing extracted components against this library, the system automatically identifies geographic features without requiring manual analysis of each image, thereby significantly improving detection efficiency and reducing time loss.
Solution Approach 2:
The patent replaces manual geographic feature identification with an automated computer-based system. The system uses image processing algorithms to extract invariant components and automatically matches them against reference data, substituting the mechanical/manual process with an automated information processing approach that is much faster and more efficient.
2Measurement precision
If detailed geographic feature data is collected, then navigation accuracy is improved, but the complexity of data collection and processing increases
Solution Approach 1:
The patent extracts only the essential invariant components from images - those features that remain consistent regardless of scale, rotation, or perspective. By focusing only on these invariant characteristics rather than collecting all possible geographic data, the system achieves accurate feature identification while simplifying the data collection and processing complexity.
Solution Approach 2:
The patent transforms image data into invariant component representations that are normalized and standardized. This parameter transformation allows the system to maintain high measurement precision for geographic features while reducing processing complexity, as the invariant components provide a consistent representation that can be directly compared against reference data without complex analysis.
3Productivity
If manual identification of geographic features is performed, then data accuracy can be verified, but the process becomes labor-intensive and slow
Solution Approach 1:
The patent implements a self-service system where the computer automatically extracts invariant components from images and identifies geographic features by comparing them against a pre-existing data library. This eliminates the need for manual intervention in the identification process, making the system both fast and operationally simple, as users only need to provide images while the system handles the complex analysis autonomously.
Data Source
AI summary
Systems, devices, features, and methods for detecting geographic features in images, such as, for example, to develop a navigation database are disclosed. For example, a method of detecting a path marking from collected images includes collecting a plurality of images of geographic areas along a path. An image of the plurality of images is selected. Components that represent an object on the path in the selected image are determined. In one embodiment, the determined components are independent or invariant to scale of the object. The determined components are compared to reference components in a data library. If the determined components substantially meet a matching threshold with the reference components, the object in the selected image is identified to be a path marking corresponding to the reference components in the data library.