Barcode Decoding Device Multiple Read Path Clustering
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Solution Overview
Problem
Automated barcode reading systems face inefficiencies due to high processing demands and limited time for decoding, often resulting in unsuccessful readings, particularly when barcodes are skewed, damaged, or obscured, leading to manual intervention and system inefficiencies.
Innovation Solution
A decoding device and method that analyze images to derive region of interest boundaries and multiple read paths based on barcode orientation, attempt readings along different paths, and cluster successful and unsuccessful attempts to identify fully read barcodes and categorize read failures, providing indications of successful readings and failure types.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If multiple read paths are attempted for each barcode, then the reliability of barcode reading is improved, but the processing time and system complexity increase
Solution Approach 1:
The system performs preliminary analysis of the captured image to identify barcode regions and their orientations before attempting readings. By pre-determining the number and angles of read paths based on barcode detection, the system avoids unnecessary reading attempts and reduces processing time while maintaining high reliability for difficult-to-read barcodes
Solution Approach 2:
The system dynamically adjusts the number and configuration of read paths based on the specific characteristics of each detected barcode, such as its orientation angle and position. This dynamic adaptation allows the system to use more read paths for skewed or damaged barcodes while using fewer paths for clearly visible, properly oriented barcodes, optimizing the balance between reliability and processing time
2Reliability
If multiple read paths are attempted for each barcode, then the reliability of barcode reading is improved, but the device complexity increases
Solution Approach 1:
The system segments the barcode reading process into distinct phases: image capture, barcode detection, read path planning, and execution. By dividing the complex task of reading skewed or damaged barcodes into manageable segments, the system can implement multiple read paths without overwhelming system complexity, as each phase handles a specific aspect of the problem independently
3Productivity
If automated reading operations are performed under high processing demand and limited time, then productivity is improved, but the reliability of reading unsuccessful barcodes deteriorates
Solution Approach 1:
The system applies different reading strategies to different barcodes based on their local characteristics. For barcodes that appear clear and properly oriented, the system uses a single standard read path to maintain high throughput. For barcodes showing signs of skew, damage, or poor positioning, the system locally adjusts by implementing multiple read paths at different angles, ensuring high reliability for difficult cases without sacrificing overall productivity
Data Source
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AI summary
A processor is configured to: analyze multiple read paths of multiple read operations to identify a cluster of read operations associated with attempts to read encoded data of a first barcode; analyze results of the cluster of read operations to identify successful read operations; in response to at least one successful read operation, provide the successfully read encoded data to another device; and in response to a lack of success among the cluster of read operations, analyze the results of the cluster of read operations to identify any read operation in which both a start end and a stop end of the first barcode were successfully read, and store, as part of a set of indications of read failures for a set of barcodes that includes the first barcode, an indication of at least whether both the start end and the stop end of the first barcode were successfully read.