Mountain Outline Restraint for Building Identification
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Solution Overview
Problem
In mountainous areas, existing methods for identifying and positioning buildings using aerial vehicles face challenges such as slow positioning, low accuracy, and high false alarm rates due to non-salient optical imaging features and complex backgrounds, leading to difficulties in guiding aerial vehicles to predetermined targets.
Innovation Solution
A method involving real-time image processing to detect and extend the mountain-based outline, conduct morphological enhancement and background suppression, perform recursive segmentation, extract local regions of interest, and directly identify and position the target building within a mountain-based outline restraint region, using techniques like binary segmentation, morphological operations, and feature verification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If full image searching is used for direct identification of the building, then the building can be identified without region constraints, but the overhead of the method becomes very high and positioning speed decreases
Solution Approach 1:
The patent divides the full image into multiple small regions based on the mountain outline, processing only relevant regions instead of the entire image. This segmentation approach reduces computational overhead while maintaining identification reliability by focusing resources on areas where buildings are likely to be located.
Solution Approach 2:
The patent extracts the mountain outline from the image and uses it to define a restraint region, thereby extracting and isolating the area of interest from the full image. This extraction process eliminates the need to process irrelevant areas, significantly reducing computational overhead and improving positioning speed.
2Ease of operation
If conventional forward-looking target identification is used to correct navigation deviation, then the method can work with simple imaging features, but identification and positioning become impossible or unreliable when optical imaging features are not salient
Solution Approach 1:
The patent applies different processing strategies to different regions: the mountain outline region receives specialized processing to extract structural features, while other regions are processed differently. This local quality approach ensures that buildings with non-salient features in the mountain region are identified reliably without complicating the overall method.
Solution Approach 2:
The patent performs preliminary extraction of the mountain outline and definition of the restraint region before conducting building identification. This preliminary action prepares the data structure and reduces complexity for the subsequent identification step, making the method both simple to operate and reliable for buildings with non-salient features.
3Reliability
If direct building identification is performed without mountain outline constraints, then false alarms may occur due to similar buildings on the same mountain, but using mountain-based outline region restraint reduces false alarms
Solution Approach 1:
The patent introduces the mountain outline as an intermediary element that mediates between the full image and the building identification process. The outline serves as a constraint that filters out false alarms from similar buildings on the same mountain while adding manageable complexity through a clear geometric boundary definition.
Data Source
AI summary
A method for identifying and positioning a building using mountain-based outline region restraint, including steps of: (1) obtaining a real-time image, detecting a mountain-based outline of the real-time image, and extending the mountain-based outline thereby obtaining a mountain-based outline restraint region, (2) conducting morphological enhancement and background suppression on the image in the mountain-based outline restraint region, (3) conducting recursive segmentation in the mountain-based outline restraint region thereby transforming an image obtained in step (2) into a binary image, (4) extracting local regions of interest of a target building in the mountain-based outline restraint region according to the binary image, and (5) directly identifying and positioning the target building in the local regions of interest.