Optical Reading Device Parallel Code Search Pipeline
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Solution Overview
Problem
Existing optical reading devices face delays in decoding results due to the time-consuming code search process, especially when dealing with large-sized images of workpieces with various codes, as they require scanning the entire image before identifying code candidates.
Innovation Solution
A stationary optical reading device that processes image data line by line, using a pre-processing circuit to calculate characteristic amounts indicating code likelihood and a processor to determine code candidate areas, allowing for parallel image capture, calculation, and decoding, thereby accelerating the output of decoding results.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the code search process scans the entire image to identify code candidates, then the accuracy of code detection is improved, but the processing time increases significantly
Solution Approach 1:
The patent divides the image processing into multiple stages: pre-processing to generate candidate areas, code search within those areas, and decoding. The pre-processing circuit identifies potential code regions by analyzing image characteristics without examining every pixel in detail, thus segmenting the search space and reducing overall processing time while maintaining detection accuracy.
Solution Approach 2:
The pre-processing circuit performs preliminary analysis of the image data before the main code search process. It calculates candidate area information and identifies potential code regions in advance, so that the subsequent code search only needs to focus on these pre-identified areas rather than scanning the entire image, significantly reducing search time.
2Adaptability or versatility
If the size of the read image is increased to capture codes on various workpieces, then the versatility and coverage are improved, but the code search time increases
Solution Approach 1:
The patent segments the large image into smaller candidate areas using the pre-processing circuit. Instead of searching the entire large image at once, the system identifies and processes only the regions that contain potential codes, making the processing time manageable even for large images while maintaining the ability to capture codes on various workpiece sizes and types.
Solution Approach 2:
The pre-processing circuit extracts and isolates potential code areas from the larger image data. By taking out only the relevant candidate regions for further processing, the system reduces the amount of data that needs to be analyzed in detail, thus reducing processing time while maintaining versatility across different workpiece sizes.
3Productivity
If parallel processing is implemented for image capture and decoding, then the processing speed is improved, but the device complexity increases
Solution Approach 1:
The patent segments the processing architecture into distinct functional units: an imaging unit for capturing images, a pre-processing circuit for candidate area identification, and a processor for decoding. These segmented components can operate in parallel at different stages of the processing pipeline, improving overall processing speed while keeping each individual component relatively simple.
Solution Approach 2:
The pre-processing circuit acts as an intermediary between the imaging unit and the processor. It receives image data from the imaging unit, performs preliminary analysis to identify candidate areas, and passes only the relevant information to the processor. This intermediary structure enables parallel processing by allowing the processor to work on decoded data while the pre-processing circuit continues analyzing new image data, thus improving productivity without requiring complex direct integration between all components.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This configuration enables immediate output of decoding results even for large images by parallel processing, reducing the time required for code search and decoding, and improving processing speed.
Implementation Method 1
an imaging unit configured to receive the light emitted from the illumination unit and reflected from the area through which the workpiece passes, to generate a read image
Data Source
AI summary
Even if a size of a read image is large, a code search process can be speeded up to enable immediate output of a decoding result. Each time a predetermined number of lines of image data is taken, a pre-processing circuit executes pre-processing on the image data and calculates a characteristic amount indicating the likelihood of the code for each area in the image data. A processor determines a code candidate area based on the acquired characteristic amount and executes a decoding process of the determined area to generate a decoding result.