Vehicular Guidance via Scan Line Crop Alignment
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Solution Overview
Problem
Existing vision systems for vehicular guidance using crop images are computationally demanding and often inaccurate due to variations in crop rows or crop edges, making them unsuitable for real-time navigation.
Innovation Solution
A vehicular guidance system that employs an imaging device to collect color image data, defines scan line segments perpendicular to the vehicle's transverse axis, and uses an image parameter evaluator and alignment detector to determine the vehicle's alignment with crop features, reducing computational resources and improving accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional vision systems are used to infer vehicle position relative to crop rows, then guidance information can be obtained, but computational resources are excessive and response time is too slow for real-time navigation
Solution Approach 1:
The patent divides the image processing task into segmented scan lines perpendicular to the vehicle's transverse axis. Instead of processing the entire image at once, the system processes individual scan lines independently to determine crop row positions, significantly reducing computational complexity while maintaining guidance accuracy
Solution Approach 2:
The patent extracts only the essential information needed for guidance by analyzing scan line parameters (such as pixel intensity variations) to detect crop row positions. This extraction approach eliminates unnecessary computational steps while preserving the key guidance data
2Reliability
If traditional vision systems process complete images to detect crop rows, then position information can be inferred, but computational complexity and processing time increase
Solution Approach 1:
The patent segments the image analysis into individual scan lines, each processed independently to detect crop row positions. This segmentation reduces the overall computational complexity from O(n²) to O(n), where n is the number of pixels, while maintaining reliable detection through systematic scanning
Solution Approach 2:
The patent uses partial action by processing only the necessary scan lines and parameters required for crop row detection, rather than analyzing all image data. This selective processing maintains guidance reliability while reducing computational burden
3Measurement precision
If vision systems rely on crop row variations for positioning, then guidance information can be derived, but accuracy decreases due to discontinuities in crop rows
Solution Approach 1:
The patent applies preliminary action by establishing a systematic scan line framework before detecting crop rows. This pre-defined scanning approach ensures consistent detection across the entire field of view, compensating for crop row discontinuities through methodical parameter evaluation across multiple scan lines
Solution Approach 2:
The patent uses feedback mechanisms where scan line parameters are continuously evaluated and compared to detect crop row positions. The systematic analysis of scan line data provides feedback that compensates for local variations and discontinuities, maintaining consistent and accurate positioning
Data Source
AI summary
The method and system for vehicular guidance comprises an imaging device for collecting color image data. A definer defines a series of scan line segments generally perpendicular to a transverse axis of the vehicle or of the imaging device. An image parameter evaluator determines scan line image parameter data for each of the scan line segments. An alignment detector (e.g., search engine) identifies a preferential heading of the vehicle that is generally aligned with respect to a crop feature, associated with the image data, based on the determined scan line image parameter meeting or exceeding a maximum value or minimum threshold value.