Optical Distance Measurement Centroid Calculation
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Solution Overview
Problem
Conventional optical distance measurement systems require significant storage space and hardware resources to calculate depth information for multiple detecting points, and they struggle with the reliability of sensed values, which affects accuracy.
Innovation Solution
The method uses centroid locations and depth information transformation functions to calculate depth values, employing filtering mechanisms like ROI, threshold, and confidence level filtering to enhance reliability, and approximates higher-degree polynomial functions with linear functions to reduce resource requirements, allowing for efficient storage and computation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional distance measurement systems use predetermined parameters for each detecting point to calculate depth information, then measurement precision is improved, but device complexity and storage requirements increase significantly
Solution Approach 1:
The patent applies universality by using a single centroid calculation module that serves all detecting points. Instead of having separate parameter sets for each detecting point, the system calculates one centroid from the sensed values and uses this single result to determine depth information for multiple detecting points through transformation functions, making the centroid calculation mechanism universal for all detection points.
Solution Approach 2:
The patent extracts the essential depth information from multiple detecting points by calculating a single centroid that represents the collective position data. Rather than processing each detecting point independently with its own parameters, the system extracts the centroid position as a consolidated representation, then derives depth information for all points from this single extracted value, significantly reducing computational and storage requirements.
2Measurement precision
If filtering mechanisms are applied to sensed values to improve reliability, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent applies preliminary action by performing filtering operations on the sensed values before centroid calculation. The system compares sensed values with threshold values and selects only those that meet confidence level criteria, preparing clean input data in advance. This preliminary filtering ensures that the subsequent centroid calculation uses only reliable data, improving measurement precision while keeping the processing structure straightforward.
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 reduces storage and hardware needs while improving accuracy by filtering out noise and using linear approximations, enabling faster and more reliable depth information calculation for multiple detecting points.
Implementation Method 1
A conventional distance measurement system captures reflection caused by light encountering an obstacle
Data Source
AI summary
An image processing method includes: acquiring a plurality of sensed values based on detecting light; comparing sensed values of each row with a corresponding threshold value to select a plurality of selected sensed values from the plurality of sensed values; determining a location of a centroid according to the plurality of selected sensed values; and calculating a plurality of depth values with respect to a plurality of detecting points according to the location of the centroid and a plurality of depth information transformation functions respectively corresponding to the detecting points.