Imaging Device Multi-Spectral Code Extraction
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Solution Overview
Problem
Existing image reading schemes face challenges in accurately extracting codes from images, particularly when multiple codes are present in a single shot, especially in scenarios involving motion and varying light conditions, which affects the accuracy and speed of information acquisition for applications like ADAS and automated driving.
Innovation Solution
The proposed solution involves an imaging device with first and second pixels sensitive to visible and non-visible light, respectively, where the image processor generates third image data by multiplying either the first or second image data by a correction factor to enhance contrast, thereby improving code extraction accuracy. This process reduces signal intensity differences and considers spectral sensitivity characteristics and sunlight spectra to optimize code detection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional image reading schemes are used to extract codes from images, then information can be acquired from one shot image or multiple codes, but code extraction accuracy deteriorates under motion and varying light conditions
Solution Approach 1:
The imaging device segments the detection task by using multiple photoelectric converters with different spectral sensitivities (first converter for first light, second converter for second light). This allows separate detection of different light components, enabling accurate code extraction even under varying light conditions and motion, as each converter optimally detects its target light wavelength range
Solution Approach 2:
The invention changes the spectral sensitivity parameter of photoelectric converters by using multiple converters with different characteristics. The first photoelectric converter has sensitivity to first light (e.g., visible light) and the second has sensitivity to second light (e.g., infrared light), allowing the system to adapt to different lighting conditions and maintain high code extraction accuracy regardless of motion or ambient light variations
2Measurement precision
If multiple photoelectric converters with different spectral sensitivities are used to improve code extraction accuracy, then measurement precision improves, but device complexity increases
Solution Approach 1:
The invention merges multiple photoelectric converters with different spectral sensitivities into a single imaging device structure. The first and second photoelectric converters are integrated in the same device, sharing common optical paths and processing circuits, which reduces overall device complexity while maintaining high code extraction accuracy through multi-spectral detection
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
The method significantly enhances code extraction accuracy and speed by increasing contrast and reducing signal intensity discrepancies, enabling reliable information acquisition for applications like ADAS and automated driving, even under challenging conditions.
Implementation Method 1
a first filter that passes a first light and a second light
Implementation Method 2
a second filter that blocks the second light
Implementation Method 3
photoelectric converters that have sensitivity to the first light and the second light; one of the photoelectric converters detects a light passing through the first filter to generate a first signal, one of the photoelectric converters detects a light passing through the first filter and the second filter to generate a second signal
Data Source
AI summary
An imaging device including a first filter that passes a first light and a second light; a second filter that blocks the second light; photoelectric converters that have sensitivity to the first light and the second light; and a processor, in which one of the photoelectric converters detects a light passing through the first filter to generate a first signal, one of the photoelectric converters detects a light passing through the first filter and the second filter to generate a second signal, and the processor performs the second light sensing based on the first signal and the second signal.