Mark Reader Image Prioritization for Decode Latency
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Solution Overview
Problem
Mark readers face significant variations in trigger-to-decode times due to differences in mark properties, lighting, and presentation, leading to inconsistent decoding performance, especially with low-contrast marks.
Innovation Solution
The implementation of a method that prioritizes images for decoding based on feature attributes such as contrast, sharpness, and orientation, allowing the reader to attempt decoding the most likely successful images first, using a first and second decode algorithm if necessary.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If images are decoded in the sequence they are acquired, then the decoding process is simple to implement, but the mean time to successful decode increases due to low-contrast and difficult-to-decode images being processed first
Solution Approach 1:
The system performs preliminary analysis of image features (contrast, sharpness, orientation, mark detection confidence) before decoding to prioritize images that are most likely to decode successfully. This preliminary sorting action reduces the mean time to successful decode by ensuring high-probability images are processed first, while maintaining manageable complexity through automated feature extraction and sorting algorithms
2Reliability
If multiple images are acquired to increase the likelihood of successful decode, then the probability of finding a decodable image increases, but the time and processing resources required increase
Solution Approach 1:
The system performs preliminary evaluation of each acquired image using feature attributes (contrast, sharpness, orientation, mark detection confidence) to predict decode success probability. This allows the system to acquire multiple images when needed but process them in optimal order, reducing overall processing time while maintaining high reliability of successful decode
Solution Approach 2:
The system dynamically adjusts image acquisition and processing parameters based on real-time analysis of image features and decode performance. By changing parameters such as priority thresholds, acquisition rates, and processing allocation based on measured image quality metrics, the system optimizes the balance between acquiring enough images for reliable decoding and minimizing time and resource consumption
Data Source
AI summary
Systems and methods for use with a mark reader that reduce the trigger-to-decode response time by prioritizing images to be decoded based on the likelihood of a successful decode are provided. A reader attempts to decode a priority image(s) first to avoid attempting to decode images that are less likely than other images to be successfully decoded. Images are rated based on feature attributes, and then prioritized for decoding. Image feature attributes are correlated with parameter groups, and the parameter groups are prioritized for use in subsequent image acquisitions.