Synchronous Reflection Sampling for Noise-Robust Object Detection
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Solution Overview
Problem
Imaging systems face challenges in accurately detecting objects in a path between a light source and an optical reflector due to environmental noise, leading to false positive or false negative detections, which can compromise weight measurements and checkout processes in bioptic barcode readers.
Innovation Solution
A system that synchronizes the measurement of reflection intensity with the expected peak intensity, accounting for measurement delays, to improve the signal-to-noise ratio and reliably determine if an object is positioned between the light source and reflector.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If continuous light reflection detection is used to monitor object presence, then detection coverage is maintained, but environmental noise increases causing false positive or false negative detections
Solution Approach 1:
The system uses periodic pulsed light emission instead of continuous illumination, with measurement windows synchronized to the expected reflection arrival time. This periodic action allows the system to distinguish between actual reflections and continuous environmental noise, improving detection reliability while maintaining coverage.
Solution Approach 2:
The system pre-determines the expected time window for reflection arrival based on the known light path distance before measurement occurs. By preparing the measurement window in advance and synchronizing it with the expected reflection timing, the system can accurately capture the reflection signal while rejecting noise that occurs at other times.
2Reliability
If reflection intensity measurement is performed without timing synchronization, then measurement simplicity is maintained, but signal-to-noise ratio decreases leading to inaccurate detections
Solution Approach 1:
The system pre-calculates and stores the expected reflection arrival time based on the known distance to the reflector before measurement occurs. This preliminary timing preparation enables synchronized measurement without requiring complex real-time calculation, balancing reliability improvement with acceptable system complexity.
Solution Approach 2:
The system creates a time-synchronized copy of the expected reflection signal window and uses it as a reference for measurement. By copying the anticipated timing pattern and comparing actual measurements against this reference window, the system achieves high signal-to-noise ratio while maintaining manageable complexity through pattern recognition rather than complex computation.
3Measurement precision
If measurement delay is not accounted for in reflection detection, then system simplicity is maintained, but detection precision decreases causing missed or false detections
Solution Approach 1:
The system pre-determines and compensates for measurement delay by adjusting the measurement window timing based on the known light travel time and system processing delay before reflection detection occurs. This preliminary delay compensation ensures that measurements are taken at the correct moment without requiring complex real-time delay calculation, improving precision while controlling complexity.
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
Enhances the accuracy of object detection by improving the signal-to-noise ratio, reducing false detections, and ensuring precise weight measurements in environments like retail checkout systems.
Implementation Method 1
a light source configured to emit a light beam
Implementation Method 2
a sensor configured to receive a reflection of the emitted light beam from the reflector
Data Source
AI summary
Techniques for improving accuracy of output of an imaging system for detecting an object between a light source and a reflector are provided. The techniques include timing a sampling of a measurement of an intensity of a reflection of a light beam based on an expected processing delay associated with the imaging system circuitry. Particularly, the sampling may be timed to occur when the expected reflection intensity is at or near its greatest magnitude, so as to improve a signal-to-noise (SNR) ratio between the expected reflection and other light manipulation (noise) introduced by an environment surrounding the imaging system. An imaging system incorporating techniques herein may be implemented, for example, in a bioptic barcode reader in a retail environment to improve object detection and weight measurement accuracy by the bioptic barcode reader.