Distance Measurement System Brightness Normalization
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Solution Overview
Problem
Conventional distance measurement systems are affected by the material of the object being detected, leading to 'depth jitter' and reduced detection accuracy due to variations in image brightness and size.
Innovation Solution
A distance measurement system that employs temporal and spatial filtering to stabilize the average brightness of object images within a predetermined range, allowing for accurate calculation of object sizes and subsequent depth determination using a lookup table.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional distance measurement systems are used, then the system structure is simple, but the detection accuracy deteriorates due to depth jitter caused by object material variations
Solution Approach 1:
The system performs preliminary actions by adjusting exposure time and gain parameters before image capture to pre-converge the brightness of object images within a predetermined range. This preliminary brightness convergence eliminates the need for complex post-processing corrections and prevents depth jitter before it occurs, thereby improving measurement precision without significantly increasing device complexity
Solution Approach 2:
The system implements feedback mechanisms by continuously monitoring the brightness of object images and adjusting exposure time and gain parameters based on the monitored brightness levels. This closed-loop feedback ensures that object image brightness remains within the predetermined range, maintaining consistent object sizes in captured images and eliminating depth jitter, thus improving depth measurement accuracy
2Measurement precision
If the system adjusts exposure time and gain for each object, then brightness convergence is achieved, but the operation time increases
Solution Approach 1:
The system applies partial action by adjusting only the necessary parameters (exposure time and gain) to achieve brightness convergence, rather than performing exhaustive adjustments. The system converges object image brightness within a predetermined range using minimal adjustments, and the processor is designed to efficiently determine object sizes without excessive computation, thus achieving brightness convergence accuracy while minimizing operation time
Solution Approach 2:
The system changes parameters (exposure time and gain) dynamically to adapt to different object materials and brightness conditions. By adjusting these parameters within optimized ranges and using efficient processing algorithms, the system achieves rapid brightness convergence without significant time loss, balancing measurement precision with operational efficiency
Data Source
AI summary
There is provided an operating method of a distance measurement system including the steps of: successively capturing image frames with an image sensor; controlling a sampling parameter to converge an average brightness value of an object image in the image frames to be within a predetermined range; calculating a plurality of first object sizes of a converged object image in a converged image frame and calculating a first average value of the first object sizes; calculating a second average value of the first average values corresponding to a plurality of converged image frames; and comparing the second average value with a lookup table to determine an object depth.