ToF Sensor Container Presence Detection Using 3D Image Analysis
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Solution Overview
Problem
Traditional imaging systems in the commercial shipping industry face challenges in accurately determining whether a Time of Flight (ToF) sensor is looking into a container, due to issues like image saturation and scatter effects caused by external light, leading to inconsistent and unreliable analytics.
Innovation Solution
A method and system that capture three-dimensional images, analyze image components, and compare them to threshold values to determine the presence or absence of a container by evaluating points external to the container boundary, ground plane height, average amplitude, and ambient values, using a Trailer Monitoring Unit (TMU) with a 3D camera and processing board.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional image analysis techniques are used to determine container presence, then the system is simple to operate, but the detection accuracy is low due to scatter effects and inability to distinguish container interiors from external environments
Solution Approach 1:
The patent segments the image analysis process into multiple distinct components: capturing raw ToF images, generating depth maps, identifying ground planes, detecting container boundaries, and analyzing interior features. Each component processes specific aspects of the image data independently, allowing for more precise container presence detection while maintaining systematic organization that manages complexity.
Solution Approach 2:
The patent transitions from traditional 2D image analysis to 3D spatial analysis by generating depth maps from ToF sensor data. This dimensional transformation enables the system to analyze depth information, ground plane heights, and container boundary positions in three-dimensional space, significantly improving the ability to distinguish container interiors from external environments like parking lots.
2Reliability
If ToF sensor captures images without container presence detection, then processing speed is fast, but reliability deteriorates due to saturated images from external light sources
Solution Approach 1:
The patent performs preliminary container presence detection by analyzing depth maps and ground plane information before conducting full container analytics. This preliminary action identifies whether a container is present in the field of view, allowing the system to avoid processing saturated images from external environments and preventing wasted computation time on invalid data.
Solution Approach 2:
The patent introduces an intermediary container presence detection module that acts as a gatekeeper between the ToF sensor and the main analytics processing. This intermediary analyzes depth information and ground plane heights to determine container presence, filtering out cases where no container is present before full analytics are applied, thereby improving reliability without excessive time loss.
3Measurement precision
If multiple image components are analyzed to determine container presence, then detection accuracy improves, but computational complexity increases
Solution Approach 1:
The patent segments the multiple image component analysis into distinct processing stages: depth map generation, ground plane identification, container boundary detection, and interior feature analysis. Each stage processes specific image components independently with dedicated algorithms, improving detection accuracy through comprehensive analysis while managing computational complexity through structured organization and modular processing.
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 enables accurate and efficient detection of container presence, reducing false positives and negatives, thereby improving the reliability of container analytics and minimizing processing waste by correctly identifying when a container is present or absent within the sensor's field of view.
Implementation Method 1
Time of Flight (ToF) sensors are frequently used to analyze the interior of shipping containers
Data Source
AI summary
Methods for detecting if a Time of Flight (ToF) sensor is looking into a container are disclosed herein. An example method includes capturing a three-dimensional image. The three-dimensional image may comprise three-dimensional point data having a plurality of points. The example method may further include analyzing the plurality of points to determine a plurality of image components. Each image component may be representative of the plurality of points. The example method may further include comparing each image component of the plurality of image components to a threshold value. Each image component may correspond to a respective threshold value. The example method may further include determining that a number of image components N of the plurality of image components satisfy the respective threshold values, and determining the presence or absence of the container by comparing the number of image components N to an agreement threshold X.