VLC Demodulation via Column Mean Thresholding
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Solution Overview
Problem
Existing VLC systems face challenges in demodulating data from small-sized light sources due to increased background noise and decreased light intensity with distance, leading to errors in data demodulation and decoding.
Innovation Solution
A method for demodulating data modulated by amplitude modulation of a light signal involves acquiring a digital image, calculating mean values per column, determining a threshold, identifying column indices, extracting a subset of mean values, and demodulating binary data from this subset.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the image sensor captures the light source zone, then the data can be demodulated, but background noise increases and light intensity decreases with distance
Solution Approach 1:
The patent segments the captured image into multiple columns and processes each column independently to calculate mean values. This segmentation allows the system to identify and extract only the relevant light source zone while excluding background areas, thereby reducing noise impact while maintaining demodulation accuracy
Solution Approach 2:
The patent applies local quality processing by calculating mean values for each column separately and identifying the specific zone corresponding to the light source based on threshold comparison. This local processing ensures that only the relevant illuminated area is used for demodulation, excluding noisy background regions
2Area of stationary object
If the light source size is small, then the device can be compact, but the zone of interest in the acquired image decreases in surface area
Solution Approach 1:
The patent transforms the 2D image data into 1D column-wise mean values, then further processes these into a simplified representation for threshold comparison. This dimensional reduction helps in efficiently identifying the light source zone even when it occupies a small area in the original image
Solution Approach 2:
The patent performs preliminary processing by calculating mean values for each column before actual demodulation. This preliminary action creates a simplified representation that makes it easier to identify the light source zone and extract relevant data, improving precision for small light sources
3Length of stationary object
If the distance between image sensor and light source increases, then the reading range is extended, but the light intensity decreases and noise increases
Solution Approach 1:
The patent implements a feedback mechanism by comparing column mean values against a threshold and dynamically identifying the light source zone boundaries. This feedback-based approach allows the system to adapt to varying distances and conditions, maintaining reliable demodulation even when light intensity decreases with distance
Solution Approach 2:
The patent changes the processing parameters by using mean value calculations and threshold-based zone identification instead of direct pixel analysis. This parameter transformation allows the system to maintain reliability across varying distances by focusing on the statistical properties of the light source zone rather than absolute intensity values
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 method improves demodulation and decoding accuracy by dynamically adapting to the light source zone, reducing the impact of background noise, and maintaining precision across varying distances and light source sizes.
Implementation Method 1
The receiver/decoder device includes an image sensor apparatus, e.g. a CMOS camera
Data Source
AI summary
The present demodulation device acquires a digital image including a zone illuminated by a light signal emitted by a source. Same is configured to:calculate (24) and store a mean value per column of said digital image, in association with a column index, arranged between a first and a second edge index of the image;determine (26) a maximum value of said mean values, and calculate a threshold from said maximum value,determine (28) of a first column index corresponding to the first mean value greater than or equal to said threshold starting from the first edge index, and of a second column index corresponding to the first mean value greater than or equal to said threshold starting from the second edge index;demodulate (30, 32) binary data from the mean values between the first column index and the second column index.