Code Candidate Ordering for Conveyor Image Decoding
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Code readers face challenges in decoding optical codes in rapid succession of images due to computational demands exceeding processor capabilities, leading to discarding of subsequent images and missed decoding opportunities.
Innovation Solution
A method where code candidates in images are ordered for decode attempts based on factors like location, travel direction, and likelihood of appearance in subsequent images, allowing the processor to prioritize decoding of candidates that are new or likely to exit the field of view first, and using different decode algorithms for different regions of interest.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If complex decode algorithms are used to compensate for imperfect image acquisition, then decoding accuracy is improved, but processing time and computational requirements increase beyond processor capabilities
Solution Approach 1:
The patent segments the field of view into multiple regions of interest (ROIs) and processes code candidates in different ROIs using different decode algorithms. Complex algorithms are applied to candidates in ROIs where they are most likely to succeed, while simpler algorithms are used in other regions, thereby reducing overall processing time while maintaining decoding accuracy for critical candidates.
Solution Approach 2:
Different decode algorithms are assigned to different regions of interest based on local characteristics. The system evaluates image quality metrics for each ROI and selects appropriate decode algorithms locally, applying complex algorithms only where necessary rather than uniformly across all candidates, thus optimizing the balance between accuracy and processing speed.
2Productivity
If images are obtained in rapid succession to increase productivity, then throughput is improved, but the processor cannot complete decoding of all candidates before the next image arrives
Solution Approach 1:
The system performs preliminary evaluation of code candidates in each ROI to identify which candidates are most likely to be successfully decoded. Based on this preliminary assessment, it prioritizes processing of high-probability candidates first, ensuring that the most promising decoding attempts are completed before the next image arrives, thereby maintaining productivity while improving decoding completion rates.
Solution Approach 2:
The patent applies decode algorithms to only a subset of code candidates in each image - specifically those in regions of interest with high likelihood of successful decoding - rather than attempting to decode all candidates. This partial action approach ensures that processing is completed within the time constraints imposed by rapid image acquisition, maintaining productivity while achieving meaningful decoding results.
3Reliability
If all code candidates in an image are processed before moving to the next image, then decoding thoroughness is improved, but subsequent images are discarded causing loss of decoding opportunities
Solution Approach 1:
The system performs preliminary identification and prioritization of code candidates in each ROI before full decoding processing. By pre-selecting high-priority candidates based on ROI characteristics and image quality metrics, the system ensures that the most important candidates are processed first, allowing decoding to be initiated on subsequent images before previous images are fully processed, thus preventing loss of decoding opportunities while maintaining thoroughness for critical candidates.
Data Source
AI summary
A method and apparatus for decoding codes applied to objects for use with a camera and a conveyor system wherein the camera includes an image sensor having a two dimensional field of view (FOV) and the conveyor system moves objects through the FOV such that objects enter the FOV along an entry edge and exit the FOV along an exit edge, the method comprising the steps of providing a processor programmed to perform the steps of obtaining images of the FOV, for each image identifying code candidates in at least portions of the image, ordering at least a subset of the code candidates for decoding in a candidate order wherein the candidate order is determined at least in part as a function of the first direction of travel through the FOV, attempting to decode code candidates in the order specified by the direction of travel and when a new image event occurs, foregoing attempts to decode at least a portion of the identified code candidates.