Adaptive Data Reader Reflective Surface Decoding
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Optical codes on highly reflective surfaces are difficult to decode due to insufficient contrast, leading to increased processing time and reduced decoding accuracy in conventional data readers.
Innovation Solution
The system dynamically adjusts operating parameters based on whether an optical code is on a reflective or non-reflective surface, optimizing illumination, decoding time, and image processing to enhance decoding efficiency and accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional data readers use fixed decoding parameters for all surfaces, then device complexity is reduced, but decoding accuracy deteriorates on highly reflective surfaces
Solution Approach 1:
The patent implements dynamic parameter adjustment by detecting surface reflectivity characteristics and automatically modifying decoding parameters in real-time. The system transitions from static fixed parameters to dynamic adaptive parameters that change based on detected surface properties, resolving the contradiction between maintaining simplicity and achieving high accuracy on varying surfaces.
Solution Approach 2:
The system changes decoding parameters such as illumination intensity, exposure time, and decoding algorithms based on detected surface reflectivity. By adjusting these parameters dynamically according to surface characteristics, the system achieves high decoding accuracy on both reflective and non-reflective surfaces without requiring multiple specialized devices.
2Measurement precision
If the system uses adaptive parameter adjustment for reflective surfaces, then decoding accuracy improves, but processing time increases
Solution Approach 1:
The system performs preliminary surface characterization by analyzing captured images to detect reflectivity properties before initiating the decoding process. This preliminary detection allows the system to pre-select appropriate decoding parameters, avoiding time-consuming trial-and-error adjustments during actual decoding and thus reducing overall processing time while maintaining high accuracy.
Solution Approach 2:
The system incorporates feedback mechanisms where decoding results are continuously monitored and used to adjust parameters for subsequent decoding attempts. This feedback loop enables the system to learn from previous attempts and optimize parameters dynamically, reducing the number of retries needed and thereby decreasing total processing time while maintaining high decoding accuracy.
3Use of energy by moving object
If fixed illumination intensity is used, then energy consumption is reduced, but image contrast deteriorates on highly reflective surfaces
Solution Approach 1:
The system dynamically adjusts illumination intensity parameters based on detected surface reflectivity characteristics. For highly reflective surfaces, the system reduces illumination intensity to prevent overexposure and maintain image contrast, while for non-reflective surfaces, it increases intensity to ensure sufficient light capture. This adaptive parameter adjustment optimizes energy consumption by using only the necessary illumination level for each surface type.
4Measurement precision
If the system processes all images with maximum decoding algorithms, then decoding accuracy is maximized, but productivity decreases
Solution Approach 1:
The system applies decoding algorithms selectively based on detected surface characteristics and code type. For simple codes on non-reflective surfaces, the system uses lighter processing, while reserving maximum decoding algorithms for complex codes on reflective surfaces where they are truly needed. This partial application of processing power maintains high decoding accuracy for challenging cases while improving overall throughput by avoiding unnecessary heavy processing for simple cases.
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 processing time, increases throughput, and improves decoding accuracy by adapting to the surface type, allowing for successful decoding of optical codes on both reflective and non-reflective surfaces.
Implementation Method 1
one or more images of an item bearing an optical code are captured
Data Source
Figure 1~1A
Figure 2A~2D
Figure 3
AI summary
Systems and methods for data reading are disclosed wherein one or more images of an item bearing an optical code are captured and the captured images are analyzed to determine whether the item has a reflective surface or not. Based on such a determination, operating parameters of the system, such as one or more of: the amount of time dedicated to 1D code decoding and the amount of time dedicated to 2D code decoding, the order in which 1D code and 2D code decoding are performed, termination of a decoding operation, restarting an image capture and decoding operation, and image preprocessing may be automatically adjusted by the system to decode an optical code.