Distance Sensor High Density Projection Pattern Artifact Detection
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Solution Overview
Problem
High-density projection patterns in distance sensors lead to complications in distinguishing individual projection artifacts due to overlap and visual noise, making accurate distance measurement challenging, especially when objects are close to the sensor.
Innovation Solution
The method involves assigning fixed windows to each projection artifact's trajectory, identifying areas of peak light intensity within these windows, and applying thresholds to exclude artifacts beyond these limits, transforming the two-dimensional problem into a one-dimensional one for rapid triangulation and distance calculation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If high-density projection patterns are used to improve measurement precision, then distance measurement accuracy is improved, but projection artifacts overlap and become difficult to distinguish
Solution Approach 1:
The patent divides the image processing task into segments by assigning fixed windows to specific trajectories of projection artifacts. Each window is dedicated to detecting artifacts along a particular trajectory, preventing overlap and confusion between artifacts from different trajectories. This segmentation allows high-density patterns to be processed accurately without artifacts becoming indistinguishable.
Solution Approach 2:
The patent transforms the two-dimensional problem of locating projection artifacts in the image plane into a one-dimensional problem by confining search to specific trajectories. By restricting the search space from the entire image to one-dimensional trajectory paths with assigned windows, the system can efficiently distinguish and detect individual artifacts even in high-density patterns.
2Measurement precision
If high-density projection patterns are used to improve measurement precision, then distance measurement accuracy is improved, but calculation time increases
Solution Approach 1:
By segmenting the image into fixed windows assigned to specific trajectories, the patent enables parallel processing of multiple trajectories simultaneously. Each trajectory can be processed independently within its assigned window, significantly reducing the overall calculation time compared to processing the entire image sequentially.
Solution Approach 2:
The patent performs preliminary action by pre-assigning fixed windows to each trajectory before image processing begins. This pre-organization of the detection space eliminates the need for complex real-time search and matching algorithms, allowing rapid identification of projection artifacts and reducing calculation time.
3Productivity
If fixed windows are assigned to each trajectory to simplify artifact identification, then detection efficiency is improved, but measurement reliability may be affected by visual noise
Solution Approach 1:
The patent applies local quality by making the detection sensitivity and window characteristics specific to each trajectory's local conditions. Each fixed window is optimized for its particular trajectory, allowing the system to maintain high detection efficiency while adapting to local variations in lighting, noise patterns, and artifact characteristics, thereby preserving measurement 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
This approach allows for reliable and efficient identification of projection artifacts, reducing calculation time and improving the accuracy of distance measurements by compensating for visual noise and overlapping artifacts.
Implementation Method 1
projection systems (e.g., comprising lasers, diffractive optical elements, and/or other cooperating components) which project beams of light
Implementation Method 2
detected by an appropriate light receiving system (e.g., lens, image capturing device, and/or other components)
Data Source
AI summary
In one example, a method includes instructing, by a processing system of a distance sensor, a pattern projector of the distance sensor to project a pattern of light onto an object, wherein the pattern comprises a plurality projection artifacts, detecting, by the processing system, a location of a first projection artifact of the plurality of artifacts in an image of the object that includes the pattern of light, wherein the detecting comprises identifying an area of peak light intensity within a window corresponding to a trajectory of the first projection artifact, wherein the trajectory represents a range of potential movement of the first projection artifact on an imaging sensor of the distance sensor, and calculating, by the processing system, a distance from the distance sensor to the object based in part on the location of the first projection artifact.