Crop Row Edge Detection Using Plan View Color Indexing
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Solution Overview
Problem
Existing crop row detection systems are prone to accuracy degradation due to disturbance factors such as varying daylight conditions and crop growth states, which affect the precision of automatic steering in agricultural machines.
Innovation Solution
A crop row detection system using an onboard camera to capture time-series color images, enhance the crop row color, generate a plan view image classified by color index thresholds, and determine edge lines for precise automatic steering control.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional image processing is used for crop row detection, then the system structure remains simple, but detection accuracy degrades under varying daylight conditions and crop growth states
Solution Approach 1:
The patent transforms the input color image through multiple parameter changes: converting RGB values to HSV color space, applying histogram equalization to enhance contrast, and using adaptive thresholding to segment crop rows from background. These parameter transformations enable accurate detection under varying lighting conditions while maintaining computational efficiency
Solution Approach 2:
The patent introduces intermediate processing steps between image capture and detection: a preprocessing module that applies filtering and enhancement, and a postprocessing module that refines detected edges. These intermediary components improve detection accuracy without requiring complete system redesign
2Adaptability or versatility
If rotation of planar perspective projection images is performed to detect work paths, then detection coverage is improved, but processing time increases
Solution Approach 1:
Instead of rotating the entire planar perspective projection image through multiple angles, the patent applies partial action by rotating only the detected edge segments or applying geometric transformation to the coordinate system. This reduces computational load while maintaining the ability to detect crop rows at various orientations
Solution Approach 2:
The patent addresses orientation detection by introducing angular dimension analysis: detecting edges in multiple directions or using Hough transform to identify line orientations. This allows the system to detect crop rows at any angle without physically rotating the image data, reducing processing time
Data Source
AI summary
A crop row detection system includes a camera mounted to an agricultural machine to image a ground surface traveled by the agricultural machine to acquire time-series color images including at least a portion of the ground surface, and a processor configured or programmed to (i) perform image processing for the time-series color images, (ii) generate, from the time-series color images, an enhanced image in which a color of a crop row for detection is enhanced to provide an enhanced image, (iii) generate from the enhanced image a plan view image as viewed from above the ground surface, the plan view image being classified into first pixels having a color index value for the crop row equal to or greater than a threshold and second pixels having the color index value below the threshold, and (iv) determine positions of edge lines of the crop row based on the color index values of the first pixels.