Camera Row Detection Using Ridge Height for Auto Steering
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Solution Overview
Problem
Existing row detection systems in agricultural machines are prone to accuracy degradation due to disturbance factors such as varying daylight conditions and crop growth states, which affect the precision of crop row detection.
Innovation Solution
A row detection system utilizing a camera and processor to perform image processing on time-series images, determining feature point movements and estimating ridge heights to enhance detection accuracy, coupled with an automatic steering controller for precise agricultural machine guidance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional row detection methods are used, then the system is simple to operate, but detection accuracy degrades under varying daylight conditions and crop growth states
Solution Approach 1:
The patent transitions from two-dimensional image analysis to three-dimensional spatial analysis by incorporating height information of crop rows. The detection system analyzes the vertical dimension (height) in addition to horizontal position, enabling accurate row detection even when crop appearance varies due to growth stage or lighting conditions. This dimensional expansion provides robustness against environmental variations.
Solution Approach 2:
The patent introduces an intermediary processing layer that converts raw image data into height information through coordinate transformation. By using the camera's optical center and focal length as reference points, the system calculates actual heights from image coordinates, creating a reliable intermediary representation that is independent of lighting and crop appearance variations.
2Duration of action of moving object
If image processing is performed under varying daylight conditions, then the system can operate throughout the day, but detection accuracy is degraded
Solution Approach 1:
The patent changes the detection parameter from color or intensity-based features to height-based features. By measuring the vertical position of crop rows relative to the ground, the system obtains a parameter that remains consistent regardless of lighting conditions or crop color changes during growth. This parameter transformation enables accurate detection throughout the day.
3Reliability
If feature point matching is used to track crop rows, then continuous tracking is achieved, but accuracy is affected by crop growth and environmental factors
Solution Approach 1:
The patent adds the height dimension to feature point tracking, creating three-dimensional tracking markers. By monitoring not only the horizontal position but also the vertical height of crop row features, the system achieves more reliable tracking that is less susceptible to appearance changes. The height information serves as an additional identifier that remains stable during crop growth.
Data Source
AI summary
A row detection system includes a camera mounted to an agricultural machine to acquire time-series images including at least a portion of a ground surface, and a processor configured or programmed to perform image processing for the time-series images, and to determine, from images among the time-series images that have been acquired at different points in time, a first amount of movement of feature points in an image plane through feature point matching, and through perspective projection of each of the feature points from the image plane onto a reference plane corresponding to the ground surface, determine a second amount of movement of each projection point in the reference plane based on the first amount of movement, and based on the second amount of movement, estimate heights of the feature points from the reference plane to detect a ridge on the ground surface.