Gradient Tree Tracing for Automated Frontal Boundary Detection
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Solution Overview
Problem
Manual delineation of frontal boundaries between fluid masses in satellite and modeled product images is time-consuming and diverts human resources.
Innovation Solution
A method using gradient generation and high gradient value tracing through a digital tree algorithm to automate the identification of frontal boundaries between fluid masses, utilizing satellite or modeled gradient images.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual delineation of frontal boundaries is performed by drawing lines on satellite images, then accurate identification of fluid mass separations is achieved, but the process becomes very time-consuming and diverts human resources
Solution Approach 1:
The patent replaces the manual mechanical process of drawing lines on satellite images with an automated computational system. The system uses gradient generation algorithms and high gradient value tracing through digital tree structures to automatically identify frontal boundaries, eliminating the need for human operators to manually delineate boundaries while maintaining identification accuracy.
Solution Approach 2:
The system enables the satellite image data to self-identify frontal boundaries through automated gradient analysis. By computing gradients and tracing high gradient value paths algorithmically, the data itself reveals the frontal boundaries without requiring external manual intervention, making the identification process self-service and automated.
2Productivity
If manual delineation methods are used for identifying frontal boundaries, then human resources can be allocated to other tasks, but the process diverts human resources from more valuable activities
Solution Approach 1:
The patent substitutes manual human operations with an automated computational system that performs gradient generation and high gradient value tracing. This replacement eliminates the diversion of human resources from more valuable activities while significantly improving the productivity and efficiency of frontal boundary identification through algorithmic automation.
3Productivity
If automated gradient tracing algorithms are implemented, then time and resource consumption is reduced, but the system complexity increases
Solution Approach 1:
The patent segments the automated tracing process into distinct modular components: gradient generation, threshold application, high gradient value identification, digital tree construction, and path tracing. This segmentation allows each component to be independently optimized and managed, reducing the perceived system complexity while maintaining high productivity in frontal boundary identification.
Solution Approach 2:
The patent introduces digital tree structures as intermediary data structures that facilitate the tracing process. These trees serve as mediators between the gradient data and the final frontal boundary identification, organizing the computation in a structured manner that manages complexity while enabling efficient automated tracing and high-speed identification.
Data Source
AI summary
A method of identifying a frontal boundary. The method may include identifying in a bounding area a first pixel having a gradient value above a threshold, generating a digital tree with the first pixel as a root node of the digital tree, and identifying based on (i) the digital tree and (ii) an orientation direction, a set of adjacent pixels with highest gradient values in proximity to the first pixel. The method may include for each adjacent pixel in the set of pixels, determining whether the corresponding gradient value is greater than a threshold, sorting one or more paths in the digital tree associated with pixels in the queue based on a respective performance measure, identifying the frontal boundary based on the one or more sorted paths, and determining based on the identified frontal boundary, a candidate frontal boundary in a new data set.