Specular Intensity Peak Detection in Lidar Systems
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Specular intensity peaks in images captured by lidar systems can lead to errors in 3D reconstruction and driving assistance due to their decorrelation with the movement of the lidar, causing erroneous image associations and vehicle trajectory determination.
Innovation Solution
A method to detect and eliminate specular intensity peaks by calculating the normal vector and incident light beam direction to identify co-linearities, and subsequently correcting for their movement-related errors using a consolidation phase.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If intensity peaks are detected in lidar images to enable 3D reconstruction and driving assistance, then the system can monitor points and reconstruct the environment, but specular intensity peaks cause errors due to their decorrelation with lidar movement
Solution Approach 1:
The patent applies local quality by analyzing the angular characteristics of each intensity peak locally. By calculating the angle between the incident light beam and the surface normal for each peak, the system identifies specular peaks through their distinctive angular properties rather than treating all peaks uniformly. This localized analysis enables differentiation between specular and diffuse reflections, improving measurement precision while maintaining reconstruction reliability.
Solution Approach 2:
The patent introduces an intermediary approach by using the surface normal vector and incident light beam direction as mediating elements to distinguish specular peaks from other intensity peaks. These intermediary calculations (normal vector computation, angle determination) serve as filtering mechanisms that separate specular reflections from diffuse reflections, allowing the system to maintain reliable 3D reconstruction by excluding erroneous specular peaks from processing.
2Quantity of substance
If specular intensity peaks are included in image processing, then more information is available for 3D reconstruction, but erroneous image associations occur due to their decorrelation with lidar movement
Solution Approach 1:
The patent applies the extraction principle by identifying and removing specular intensity peaks from the set of detected peaks before processing. Through angular analysis comparing the incident light beam direction with the surface normal, the system extracts and eliminates specular peaks that would cause erroneous associations. This selective extraction maintains the quantity of useful diffuse reflection peaks while ensuring the reliability of image associations in 3D reconstruction.
3Device complexity
If conventional intensity peak detection methods are used, then the processing is simple, but specular peaks cause erroneous trajectory determination
Solution Approach 1:
The patent applies parameter changes by introducing angular parameters (angle between incident light beam and surface normal) to the peak detection process. Instead of using only intensity thresholds or simple spatial filters, the system incorporates angular characteristics to identify and exclude specular peaks. This parameter enhancement increases measurement precision for trajectory determination while maintaining reasonable algorithm complexity through vector-based calculations that are computationally efficient.
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 enhances the reliability and accuracy of image processing by distinguishing and correcting for specular intensity peaks, reducing errors in 3D reconstruction and driving assistance systems.
Implementation Method 1
Reflection of the laser beam by the surface of the target is detected by receivers in the lidar
Implementation Method 2
specularly: direction of the reflected ray symmetrical with the ray emitted relative to the normal to the surface
Implementation Method 3
receivers in the lidar... record the time elapsed between the moment at which the laser pulse was emitted and that at which it was received by the sensor
Data Source
AI summary
A method for identifying at least one intensity peak of a specularly reflected light beam including: a step (E1) of detecting at least one intensity peak of a light beam present in a first image taken at instant t; a step (E2) of calculating a vector (N) normal to a surface at each point of the first image associated with an intensity peak detected in step (E1); a step (E3) of calculating a vector (L) of the direction of the incident light beam at each point of the first image taken at instant (t), associated with an intensity peak detected in step (E1); a step (E4) of determining the co-linearity between the normal vector (N) and the vector (L) of the direction of the incident light beam in order to identify an intensity peak of the specularly reflected light beam.