Optical Wheel Alignment Using Hough and Radon Transforms
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Solution Overview
Problem
Conventional wheel alignment techniques require capturing a large number of images, which is resource-intensive and time-consuming, especially when using multiple laser lines, and often involve manual labor for rim identification.
Innovation Solution
A non-contact optical system captures a plurality of images of a wheel using LED and laser light sources, processes them using techniques like Hough transform and Radon transform to automatically identify the rim and determine alignment, reducing the need for multiple images and manual intervention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple laser lines are used for wheel alignment detection, then measurement precision is improved, but use of energy and processing time increase
Solution Approach 1:
The patent extracts and processes only the essential features from captured images using Hough transform for circle detection and Radon transform for line detection. This selective extraction of critical geometric features enables accurate alignment measurement without requiring multiple laser lines, thereby reducing energy consumption while maintaining measurement precision.
Solution Approach 2:
The patent changes the approach from using multiple laser lines to using image processing parameter transformations (Hough transform parameters for circles, Radon transform parameters for lines). This parameter-based approach achieves the same measurement precision with a single laser line or fewer lines, significantly reducing energy consumption.
2Measurement precision
If multiple images are captured for wheel alignment, then measurement precision is improved, but productivity decreases
Solution Approach 1:
The patent performs preliminary image processing by applying Hough transform and Radon transform to extract geometric features from a single captured image. This preliminary extraction of rim and laser line positions eliminates the need for multiple image captures and sequential processing, thereby improving productivity while maintaining measurement precision through robust mathematical transforms.
Solution Approach 2:
The patent replaces the mechanical approach of capturing multiple images with a mathematical transformation approach. By using Hough transform and Radon transform on a single image, the system achieves the same measurement precision that would otherwise require multiple captures, significantly improving processing speed and productivity.
3Measurement precision
If manual rim identification is performed, then ease of operation is reduced, but measurement precision can be maintained
Solution Approach 1:
The patent implements self-service by enabling the system to automatically identify the wheel rim and laser lines through image processing algorithms. The Hough transform automatically detects circular rim structures, and the Radon transform automatically identifies laser line positions. This automated self-identification eliminates manual intervention while maintaining high measurement precision, significantly improving ease of operation.
Solution Approach 2:
The patent replaces manual rim identification with automated mathematical transformation methods. The Hough transform and Radon transform automatically extract geometric features from images, substituting human visual inspection and manual measurement with robust computational algorithms that maintain precision while eliminating operational complexity.
4Reliability
If conventional alignment equipment is used, then reliability is maintained, but device complexity increases
Solution Approach 1:
The patent replaces complex mechanical alignment equipment with an optical imaging system combined with mathematical transformations. Instead of using multiple laser lines and complex mechanical detection apparatus, the system uses a single imaging device with Hough and Radon transforms to achieve reliable alignment detection, significantly simplifying device complexity while maintaining reliability.
Solution Approach 2:
The patent changes from a multi-parameter mechanical detection system to a parameter transformation-based optical system. By using mathematical transforms (Hough parameters for circles, Radon parameters for lines) on image data, the system achieves the same reliability with fewer physical components, reducing device complexity while maintaining detection reliability.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The system achieves accurate and fast wheel alignment with minimal resource consumption, determining toe, camber, and caster angles with high precision in a single frame, reducing processing time and operational costs.
Implementation Method 1
an image capturing device to capture images of the wheel
Data Source
AI summary
A method for aligning wheels of a vehicle is described herein. In an implementation, a plurality of images of a wheel of the vehicle is captured. The plurality of images comprises a LED image of the wheel, a laser image of the wheel, and a control image of the wheel. The method further comprises identifying, automatically, a rim coupled to the wheel based on the plurality of images. Further, the wheel is aligned based on the identified rim.