Optical Code Reading with Priority Decoding Across Image Sequences
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Solution Overview
Problem
Existing code reading systems face inefficiencies in processing image sequences due to real-time constraints and varying image quality, leading to missed code readings and wasted processing time on difficult images, especially when early images contain code fragments or poor optical conditions.
Innovation Solution
A code-reading device and method that utilizes a control and evaluation unit with multiple processing units to prioritize and parallel process code image areas across an image sequence, scoring and queuing them based on likelihood of readability, ensuring optimal utilization of processing time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If images are processed in chronological order of acquisition, then processing can begin as soon as the first image is available, but valuable decoder time is wasted on difficult images and more promising code image areas in later images remain unprocessed
Solution Approach 1:
The patent implements dynamic image selection by evaluating multiple images and their code image areas, then adaptively selecting which images to process based on current processing time and success probability. The system transitions from static chronological processing to dynamic priority-based processing, where the processing order changes based on real-time assessment of code readability and processing constraints.
Solution Approach 2:
The system changes the parameter of processing order from fixed chronological sequence to variable priority sequence. By introducing parameters such as code reading success probability and processing time consumption, the system dynamically adjusts which images are processed and in what order, optimizing the balance between throughput and success rate.
2Measurement precision
If the decoder uses aggressive algorithms and error correction for code fragments, then reading accuracy improves, but processing time increases significantly
Solution Approach 1:
The patent applies different processing strategies to different code image areas based on their local characteristics. For high-quality code areas with good readability, standard decoding is used. For fragmented or difficult code areas, the system selectively applies aggressive algorithms and error correction only when necessary and when time permits, rather than uniformly applying complex algorithms to all code areas.
Solution Approach 2:
The system implements partial action by selectively applying aggressive decoding algorithms only to specific code image areas that warrant additional processing effort. Instead of applying full error correction and aggressive algorithms to all code fragments, the system judiciously applies these methods only where needed based on code quality assessment and remaining processing time, optimizing the trade-off between accuracy and time consumption.
3Adaptability or versatility
If multiple code readers are used to capture objects from multiple sides, then code detection coverage improves, but system complexity and processing load increase
Solution Approach 1:
The patent merges the processing of code image areas from multiple code readers into a unified evaluation framework. Instead of independently processing images from each reader, the system combines all code image areas from multiple sources, evaluates them together based on their reading success probability and processing time requirements, and selects the best candidates for decoding. This reduces redundancy and optimizes the use of processing resources across the multi-reader system.
Data Source
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AI summary
A code reading device (20) for reading optical codes is specified, which device has an image sensor (24) for recording images of at least one object (14) with at least one optical code, and a control and evaluation unit (26) which is designed to record a plurality of images in succession, to locate code image regions (20) in the images, each of which contains a candidate for an optical code, and to process the code image regions (20) using at least one decoder method in order to read the optical code of the code image region (20) and to select a processing sequence of the code image regions (20) using the at least one decoder method across several images of the plurality of images.