Sheet of Light Position Detection Using Derivative Zero-Crossings
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing methods for detecting the position of a laser beam in images are sensitive to background intensity variations, dependent on window size selection, and lack robustness with saturated peaks and varying peak widths, making them unsuitable for accurate 3D measurement and reconstruction.
Innovation Solution
A method using a derivative filter of size S, set to at least the width of the widest peak, applied to an intensity profile within a region of interest defined by intensity differences and a threshold, to detect zero-crossings and determine the position of a sheet of light, improving robustness and accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a window of fixed size is used to detect laser peak position, then the detection process is simplified, but the method becomes sensitive to background intensity variations and lacks robustness with saturated peaks and large variations in peak widths
Solution Approach 1:
The patent applies dynamics by making the window size adaptive rather than fixed. The window size automatically adjusts based on the detected peak width, allowing the detection algorithm to maintain optimal performance across varying peak conditions without manual intervention, thus resolving the contradiction between simplicity and robustness
Solution Approach 2:
The patent changes the parameter of window size dynamically based on the intensity profile characteristics. By adjusting the window size parameter according to the actual peak width detected in the intensity profile, the method maintains reliability across different peak conditions while keeping the overall detection process relatively simple
2Reliability
If the window size is increased to capture wider peaks, then detection robustness improves, but the precision of position detection decreases due to including more background pixels
Solution Approach 1:
The patent uses dynamics by making the window size adaptive rather than fixed. The window size automatically adjusts based on the detected peak width, allowing the detection algorithm to maintain optimal performance across varying peak conditions without manual intervention, thus resolving the contradiction between simplicity and robustness
Solution Approach 2:
The patent applies local quality by adjusting the window size locally according to the specific peak characteristics in different regions of the intensity profile. Each peak receives a customized window size based on its width, ensuring optimal detection precision for each local condition rather than applying a uniform window size globally
3Device complexity
If center of gravity method is used for position detection, then calculation is straightforward, but the method is very sensitive to variations in background intensity (DC offset)
Solution Approach 1:
The patent extracts and removes the background intensity component from the detection process. By using zero-crossing detection on the derivative of the intensity profile, the method isolates the peak position information from the background DC offset, effectively eliminating the harmful sensitivity to background variations while maintaining calculation simplicity
Solution Approach 2:
The patent substitutes the center of gravity calculation method with a derivative-based zero-crossing detection method. This replacement eliminates the mathematical operation that is sensitive to background intensity (the weighted average calculation) while maintaining computational efficiency through simpler derivative and zero-crossing operations
Data Source
AI summary
In a method and system for detecting a position of a sheet of light in an image, two parameters are used, namely the width of the widest peak to be detected and the intensity difference of the least-contrasted peak to be detected. From these two parameters, a size S, a distance D, and a threshold T are determined. A region of interest (ROI) is determined based on the intensity profile associated with a line of pixels of the image, distance D and threshold T. A derivative filter of size S is applied to the intensity profile to produce a slope of the intensity profile. In the determined ROI, one or more zero-crossings in the slope of the intensity profile are detected. From the detected zero-crossings, a zero-crossing is selected and the position of the selected zero-crossing is returned as the detected position of the sheet of light for the line of pixels.