Imaging Barcode Detection Using Segmented Search Sequences
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Solution Overview
Problem
Conventional laser scanners struggle with scanning barcodes that are not aligned with their scan lines, particularly on smaller items and cannot efficiently scan two-dimensional barcodes, while imaging scanners have long processing times, making them unsuitable for swipe scanning.
Innovation Solution
An imaging device divides an image into a predetermined number of areas and uses a specific search sequence to analyze them efficiently, switching to a new image only when a time limit is reached or the barcode is detected, allowing for effective identification of one- or two-dimensional barcodes regardless of alignment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a spiral search pattern is used to locate the barcode in an image, then the barcode can be found regardless of its position, but the processing time becomes too long
Solution Approach 1:
The image is divided into multiple blocks (e.g., 4x4 grid), and the search is segmented to focus on specific blocks based on motion direction. Instead of searching the entire image sequentially, the system divides the search space into manageable segments and selectively searches relevant segments, reducing overall processing time while maintaining detection reliability.
Solution Approach 2:
The system performs preliminary actions by predicting the likely location of the barcode based on motion direction before actually searching. The search sequence is predetermined based on expected barcode positions, allowing the system to jump directly to relevant areas rather than performing a complete sequential search, thus reducing processing time.
2Reliability
If the imaging scanner analyzes every image sequentially, then no barcode is missed, but intermediate images are skipped and barcodes may pass through undetected
Solution Approach 1:
The search strategy dynamically adapts based on motion direction. The system adjusts the search sequence and block selection according to the detected motion characteristics, making the search process dynamic rather than static. This allows the system to maintain high detection reliability while operating at higher speeds by focusing computational resources on the most relevant image regions.
Solution Approach 2:
The system selectively skips certain image blocks that are unlikely to contain the barcode based on motion direction analysis. By rushing through irrelevant blocks and focusing on high-probability areas, the system maintains productivity while ensuring barcodes are not missed in critical regions.
3Device complexity
If laser scanners use fixed scan lines, then the scanning mechanism is simple, but barcodes not aligned with scan lines cannot be successfully scanned
Solution Approach 1:
The patent replaces the mechanical laser scanning system with an imaging-based detection system. Instead of using physical scan lines that require precise mechanical alignment, the system uses a camera to capture the entire field of view and processes the image digitally to locate barcodes. This substitution eliminates the alignment limitation while keeping the overall system relatively simple.
Solution Approach 2:
The system transitions from one-dimensional linear scan lines to two-dimensional image processing. By capturing the entire scene in 2D and then analyzing it, the system gains the ability to detect barcodes at any orientation and position without requiring mechanical adjustment of scan lines, thus improving adaptability while maintaining simplicity.
Data Source
AI summary
Described is a method of locating a predetermined pattern. An image is divided into a predetermined number of areas. A search sequence indicative of an order in which the areas are to be analyzed for the predetermined pattern is determined. The areas in the search sequence are analyzed until either a predetermined time elapses or the predetermined pattern is detected. When the predetermined time has elapsed before the predetermined pattern is detected, a further image is obtained. Then, areas remaining in the sequence are analyzed in the further image beginning with an area to be analyzed immediately after a last analyzed area of the image until either the predetermined time elapses or the predetermined pattern is detected in one of the remaining areas.