Barcode Reader Color Image Processing Pipeline
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Solution Overview
Problem
Color bar code readers face challenges in contrast and resolution due to the lower number of color pixels compared to monochrome sensors, leading to information loss during demosaicing, which affects decoding accuracy and distance.
Innovation Solution
A method for color image processing in barcode readers that involves analyzing raw and processed image data using statistical analysis and image processing techniques such as demosaicing, filtering, and edge detection to determine the optimal data set for decoding, potentially bypassing the need for demosaicing to maintain image quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If demosaicing is performed on raw image data from color sensors, then color information is reconstructed and a complete color image is produced, but image contrast and modulation are reduced leading to information loss
Solution Approach 1:
The system dynamically selects between processing raw image data directly or performing demosaicing based on real-time analysis of image characteristics and decoding requirements. This dynamic approach allows the system to adapt to different barcode types and lighting conditions, choosing the optimal processing path to maintain both color information completeness and image contrast.
Solution Approach 2:
The patent changes the processing parameters by analyzing statistical properties of the raw image data (such as spatial frequency content, chromatic content, spatial resolution, sharpness, and contrast) and adjusting the processing pipeline accordingly. This parameter-based decision-making enables the system to preserve image quality while recovering color information when necessary.
2Adaptability or versatility
If color sensors are used to read barcodes, then color imaging capability is achieved, but the number of color pixels is fewer compared to monochrome pixels resulting in lower contrast and resolution
Solution Approach 1:
The patent segments the image processing pipeline into multiple analysis stages, evaluating different aspects of the raw image data (spatial frequency, chromatic content, resolution, sharpness, contrast) separately. This segmentation allows the system to identify specific deficiencies in color sensor performance and apply targeted processing strategies to compensate for lower pixel density while maintaining color imaging capability.
Solution Approach 2:
The system introduces an intermediary analysis stage between raw image capture and decoding that evaluates image quality metrics and determines the optimal processing path. This intermediary layer acts as a mediator that bridges the gap between color sensor limitations and decoding requirements, selecting whether demosaicing or direct processing yields better results for the specific barcode being scanned.
3Ease of manufacture
If traditional processing methods are used for color imaging, then color images are produced, but there is a relative loss of information compared to monochrome imaging technology
Solution Approach 1:
The system performs preliminary statistical analysis on the raw image data before committing to a processing path. By analyzing spatial frequency content, chromatic content, spatial resolution, sharpness, and contrast in advance, the system can determine whether demosaicing will preserve or lose information for the specific image at hand, preventing irreversible information loss before it occurs.
Solution Approach 2:
The patent implements a feedback mechanism where the results of preliminary image analysis feed into the decision-making process for selecting the processing path. The system uses the analyzed characteristics (spatial frequency, chromatic content, resolution, sharpness, contrast) to feedback into the processing selection, ensuring that the chosen method minimizes information loss for that specific image while maintaining ease of color imaging implementation.
Data Source
AI summary
Methods and devices for performing color imaging processing on the fly for barcode readers are disclosed herein. An example method includes color image processing in a barcode reader to identify one of raw image data or processed image data and further decoding indicia in the identified raw or processed image data. The method includes receiving a raw image data of an image of an object, performing image processing on the raw image data, analyzing the raw image data and the processed image data, and identifying which of the raw image data or processed image data to communicate to a decoder for further decoding. The decoder then identifies, in the identified raw image data or processed image data, indicia corresponding to an object, and decodes the identified indicia.