Structured Illumination Edge Detection for Textured Surfaces
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Solution Overview
Problem
Machine vision inspection systems face challenges in reliably detecting edge features on workpieces with highly textured surfaces or near surface features like chamfers, due to limitations in conventional edge detection methods which are sensitive to unwanted reflections and surface textures.
Innovation Solution
A machine vision inspection system utilizing a light stripe projection system that projects focused light stripes across the edge feature, analyzing the changing width and intensity of these stripes to determine the edge location with sub-pixel accuracy, regardless of surface textures or features.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional edge detection methods are used, then the system can detect edges on smooth surfaces, but the detection reliability deteriorates on highly textured surfaces or near surface features like chamfers due to unwanted reflections
Solution Approach 1:
The patent applies local quality by making the illumination localized to a thin stripe rather than uniform across the entire field. This focused stripe illumination isolates the measurement region from surrounding surface textures and features, allowing edge detection to proceed reliably even on textured surfaces. The stripe acts as a localized probe that minimizes interference from adjacent areas.
Solution Approach 2:
The patent introduces a light stripe as an intermediary element between the illumination source and the edge detection process. This light stripe serves as a mediator that carries height information through its intensity and width variations, enabling edge detection while filtering out unwanted surface texture effects. The stripe acts as a controlled interface for extracting edge information.
2Measurement precision
If conventional illumination is used, then the setup is simple, but edge detection precision deteriorates due to sensitivity to surface reflections and textures
Solution Approach 1:
The patent changes the illumination parameters from uniform broad illumination to a focused stripe pattern. This parameter change in the illumination geometry transforms how surface information is captured, converting height variations into measurable intensity and width changes in the light stripe. This enables precise edge location by analyzing the stripe's interaction with the edge rather than relying on conventional reflection-based methods.
Solution Approach 2:
The patent adds a dimensional aspect to illumination by using a stripe (one-dimensional line) rather than uniform areal illumination. This dimensional change allows the system to probe the surface along a specific line, reducing the problem from two-dimensional surface analysis to one-dimensional stripe analysis, thereby improving edge detection precision while managing system complexity.
3Loss of information
If broad uniform illumination is used, then the lighting setup is simple, but the ability to detect height changes across edges deteriorates
Solution Approach 1:
The patent applies local quality by concentrating illumination into a narrow stripe rather than distributing it uniformly. This localized illumination interacts with height changes across the edge, causing measurable variations in stripe intensity and width as the stripe crosses from one surface height to another. This preserves height change information that would be lost in uniform illumination.
Solution Approach 2:
The patent changes the illumination parameter from uniform intensity distribution to a concentrated stripe pattern. This parameter change enables the illumination to act as a height-sensitive probe, where variations in stripe appearance directly encode surface height information across the edge, preventing loss of critical measurement data.
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
This method provides robust and accurate edge detection, even in the presence of surface textures and features that disrupt conventional edge detection methods, achieving reliable and precise edge location.
Implementation Method 1
projecting a focused light stripe across a workpiece
Implementation Method 2
acquire an image of the light stripe
Data Source
AI summary
A machine vision inspection system (MVIS) and a related light stripe edge feature location method are disclosed. The MVIS comprises a control system, a light stripe projection system, an imaging system, and a user interface. In a region of interest including the edge feature, the light stripe projection system focuses a light stripe transverse to the edge direction and across the edge feature, such that the light stripe has a changing stripe intensity profile along the light stripe. The imaging system acquires an image of the light stripe and the control system analyzes the image to determine the location of the edge feature based on a changing light intensity profile along the stripe. The method may be implemented in an edge detection video tool. The method may be advantageous for inspecting highly textured, beveled, chamfered, rounded or damaged edges, for example.