Image Preprocessing for Embedded Element Decoding
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Solution Overview
Problem
Existing image processing technologies face challenges in efficiently decoding embedded elements in cluttered images, particularly in resource-constrained environments such as portable devices, due to high computational resource requirements.
Innovation Solution
A method for preprocessing images that involves selecting a color channel, processing it to generate data distribution information, determining a threshold, and generating an output image to enhance the embedded element and suppress other elements, thereby reducing computational resources needed for decoding.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If image processing is performed on cluttered images to decode embedded elements, then decoding capability is improved, but computational resource consumption increases
Solution Approach 1:
The patent segments the image processing task by separating the embedded element of interest from the cluttered background through color channel selection and thresholding. By focusing processing only on the relevant color channel and region, the system reduces computational resource consumption while maintaining decoding capability.
Solution Approach 2:
The patent extracts the embedded element from the cluttered image by selecting specific color channels and applying thresholds to isolate the element of interest. This extraction approach removes unnecessary background information, reducing the computational burden on resource-constrained devices.
2Loss of time
If color channel selection and thresholding are applied to preprocess images, then processing time is reduced, but image quality may be affected
Solution Approach 1:
The patent applies local quality enhancement by selectively processing only the color channel and region containing the embedded element, rather than processing the entire image uniformly. This localized approach reduces processing time while maintaining image quality in the critical regions.
Solution Approach 2:
The patent performs preliminary color channel selection and thresholding to preprocess the image before decoding. This preliminary action simplifies the image data structure and reduces processing time for subsequent decoding operations, while maintaining sufficient image quality for accurate element extraction.
3Measurement precision
If full image processing is performed on resource-constrained devices, then decoding accuracy is maintained, but device performance deteriorates
Solution Approach 1:
The patent applies partial action by processing only the necessary color channel and region containing the embedded element, rather than performing full image processing. This partial approach maintains decoding accuracy for the target element while improving device performance by reducing computational workload.
Solution Approach 2:
The patent changes processing parameters by selecting specific color channels and adjusting thresholds to optimize for the embedded element characteristics. These parameter changes enable the system to maintain decoding accuracy while reducing overall processing requirements, thereby improving device performance on resource-constrained hardware.
Data Source
Figure 1
Figure 2A~2B
Figure 2C-1
AI summary
At least some embodiments of the present disclosure directs to a method for processing an input image having an embedded element, comprising the steps of: computing one or more histograms of the input image; identifying a range of interest in one of the one or more histograms; and determining, by the processor, a threshold based on the range of interest. In some embodiments, a computing device processes the input image using the threshold to generate an output image.