Ridge Shape Evaluation by Cross-Section Image Comparison
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Solution Overview
Problem
Existing agricultural traveling vehicles are unable to evaluate the shape of formed objects, such as ridges, on agricultural fields to determine their acceptability.
Innovation Solution
An evaluation system and method that utilize an arithmetic processor to compare a template image with a cross-sectional image of a geographical feature, determining shape acceptability by analyzing contour differences and generating contour difference images.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If an agricultural traveling vehicle is equipped with a direction identifier to identify the direction of a ridge, then the vehicle can travel in the correct direction along the ridge, but the vehicle cannot evaluate whether the shape of the ridge is acceptable
Solution Approach 1:
The patent replaces manual visual inspection and mechanical measurement methods with an automated image processing system. The arithmetic processor captures images of the ridge, generates cross-sectional images through image processing, and automatically compares them with template images to evaluate shape acceptability, eliminating the need for manual measurement tools and expert inspection.
Solution Approach 2:
The patent introduces cross-sectional images as an intermediary representation between the physical ridge and the evaluation process. By generating cross-sectional views from captured images and comparing them with template cross-sectional images, the system creates a standardized intermediate format that facilitates objective shape evaluation without requiring direct physical measurement of the complex three-dimensional ridge structure.
2Measurement precision
If manual inspection methods are used to evaluate ridge shape, then equipment complexity is low, but evaluation accuracy and consistency are poor
Solution Approach 1:
The patent implements a feedback mechanism where the arithmetic processor compares the actual ridge cross-sectional image with the template cross-sectional image, determines shape acceptability based on the comparison results, and can provide this evaluation feedback to guide subsequent agricultural operations. This automated feedback loop ensures consistent and accurate evaluation criteria are applied uniformly.
Solution Approach 2:
The patent creates a digital copy (cross-sectional image) of the physical ridge structure through image processing. This digital replica can be stored, analyzed, and compared with template images without altering the original ridge, enabling precise measurement and evaluation while maintaining a permanent record for quality control and traceability.
3Measurement precision
If the evaluation system compares template image with cross-sectional image to determine shape acceptability, then evaluation accuracy improves, but processing time increases
Solution Approach 1:
The patent prepares template cross-sectional images in advance that represent acceptable ridge shapes. By having these reference templates pre-established, the evaluation process only requires comparing captured images against the stored templates, significantly reducing processing time compared to performing full shape analysis or manual inspection during field operations.
Solution Approach 2:
The patent extracts only the essential cross-sectional features from the captured ridge images for comparison with templates. By focusing evaluation on the critical cross-sectional shape characteristics rather than analyzing the entire three-dimensional structure or all image details, the system achieves accurate evaluation with minimal processing time.
Data Source
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AI summary
An evaluation system (S) includes an arithmetic processor (20c) configured or programmed to evaluate a shape of a formed object formed by a working device (2) on an agricultural field, based on matching between a template image and a cross-sectional image of a geographical feature including the formed object.