Camera Code Reader Automatic Setup via Virtual Image Analysis
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Solution Overview
Problem
Existing code reading systems face challenges in optimizing settings for dynamic operations, especially when objects are in motion and varying heights, leading to suboptimal reading rates due to the complexity and expense of manual setup and the limitations of fixed focus systems.
Innovation Solution
A method for automatically setting up a camera-based code reading device using an image sensor and control unit, which generates virtual example images to optimize recording and decoding parameters, allowing for dynamic adaptation to different object sizes and motion, thereby improving reading rates without requiring expert knowledge or manual intervention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual setup and optimization is performed by an expert, then the code reading system can be optimized for its application, but the process becomes extremely complex and expensive
Solution Approach 1:
The code reading system performs self-optimization through automatic setup procedures that evaluate reading results and adjust parameters autonomously without requiring expert manual intervention. The system tests different parameter combinations and configurations automatically, selecting the optimal settings based on measured reading rates and performance metrics.
Solution Approach 2:
The system automatically adjusts multiple parameters including camera exposure settings, decoder configuration, image processing parameters, and focal position to optimize code reading performance. These parameter changes are performed systematically through automated testing and evaluation of different configurations.
2Device complexity
If a fixed focus system or slow focus system is used, then the device structure is simpler, but dynamic adaptation to individual objects at different heights is not possible
Solution Approach 1:
The system implements dynamic focus adjustment that adapts to individual objects at different heights during operation. The focal position is automatically modified based on detected object distance and height, enabling the fixed or slow focus system to achieve dynamic adaptation capabilities without requiring a complete autofocus system redesign.
Solution Approach 2:
The system performs preliminary optimization during setup by determining optimal focal positions and focus adjustment parameters for expected object height ranges. This preliminary configuration enables faster operation during actual code reading without requiring real-time complex calculations.
3Adaptability or versatility
If multiple configurations for different objects are stored in different parameter banks, then various object types can be accommodated, but the decoding process slows down due to iteration through configurations
Solution Approach 1:
The system uses feedback from initial decoding attempts to quickly identify the most suitable parameter configuration without iterating through all stored configurations. Reading results and performance metrics are analyzed to select the optimal configuration, reducing the time spent on configuration searching while maintaining adaptability to different object types.
Solution Approach 2:
The system performs preliminary classification and configuration selection based on object characteristics detected during setup and initial scanning. By pre-grouping configurations according to object types and characteristics, the system can quickly retrieve the appropriate parameter set without exhaustive searching during actual decoding operations.
4Stability of the object's composition
If gradual parameter adaptations are performed during operation, then drift and changes can be compensated, but the adaptation is too slow for highly dynamic reading situations
Solution Approach 1:
The system implements dynamic parameter adaptation that adjusts the speed and magnitude of parameter changes based on the detected situation. For stable reading conditions, gradual adjustments maintain stability, while for highly dynamic situations with significant performance drops, the system performs faster, more dramatic parameter adaptations to quickly restore optimal reading rates.
Solution Approach 2:
The system monitors reading performance metrics and automatically adjusts parameters including exposure time, gain, focal position, and decoder settings based on the rate and magnitude of performance degradation. These parameter changes are adapted to the specific dynamic conditions observed during operation.
Data Source
AI summary
A method of automatically setting up a code reading device that has an image sensor and a control and evaluation unit, wherein an example image of an example object arranged in the field of view of the image sensor and having an example code is recorded by the image sensor and at least one recording parameter and/or at least one decoding parameter for the operation of the code reading device is set with reference to an evaluation of the example image. In this respect, further example images are generated from the example image by calculational variation and the at least one recording parameter and/or the at least one decoding parameter is/are set with reference to an evaluation of the further example images.