Watermark Decoding via Image Segmentation and Content Analysis
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Solution Overview
Problem
Camera-based systems in retail and industrial settings face challenges in efficiently processing and identifying machine-readable indicia, such as digital watermarks, due to limited processing time and resource constraints, especially when dealing with composite images captured from multiple viewpoints.
Innovation Solution
The technology involves analyzing reference imagery to determine high-probability areas for decodable watermark data, downsampled image regions, and applying image distortion correction and signal decoding based on content detection, using methods like establishing subareas, determining image characteristics, and comparing them to baseline values to classify areas as background or content, thereby reducing processing time and resource use.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the camera system processes entire image frames to decode watermarks, then decoding accuracy is maintained, but processing time and resource consumption increase significantly
Solution Approach 1:
The patent divides the image frame into multiple smaller image areas (e.g., 4-16 regions) and further segments each area into subareas (e.g., 4-9 subareas per image area). This segmentation allows the system to process only relevant portions of the image that contain watermarks, rather than analyzing the entire image frame, thereby reducing processing time while maintaining decoding accuracy.
Solution Approach 2:
The patent applies different processing strategies to different regions of the image based on their content characteristics. By analyzing image characteristics (such as contrast, texture, or pattern recognition) to identify which image areas are more likely to contain watermarks, the system allocates processing resources selectively to high-probability regions, improving efficiency without sacrificing overall accuracy.
2Reliability
If the system analyzes all image areas for watermark content, then complete coverage is achieved, but computational resource consumption increases
Solution Approach 1:
The patent performs preliminary analysis of image characteristics (such as calculating mean intensity, standard deviation, or detecting edge patterns) on each image area before committing to full watermark decoding. This preliminary action filters out areas unlikely to contain watermarks, allowing the system to maintain detection completeness while reducing computational resource consumption by skipping detailed analysis of irrelevant regions.
Solution Approach 2:
The patent applies partial action by processing only a subset of image areas that have the highest probability of containing watermarks, rather than uniformly processing all areas. The system uses heuristic criteria (such as contrast thresholds or pattern recognition) to identify and process only the most promising regions, achieving sufficient detection reliability without the full computational cost of analyzing every pixel.
3Speed
If the camera system processes images in real-time, then operational speed is maintained, but processing complexity increases due to limited processing windows
Solution Approach 1:
The patent segments the image processing task into discrete, manageable stages: (1) dividing the image frame into image areas, (2) analyzing image characteristics of each area, (3) selecting high-probability areas for decoding, and (4) extracting watermarks. This segmentation enables the system to complete processing within real-time constraints by breaking down the complex task into sequential operations that can be executed efficiently.
Solution Approach 2:
The patent uses partial action by implementing simplified processing steps that are sufficient for real-time operation. Instead of performing exhaustive analysis of all image regions, the system applies heuristic filters and processes only the most promising areas, reducing algorithmic complexity while maintaining acceptable processing speed for real-time applications.
Data Source
AI summary
The present technology relates to image signal processing. One aspect of the present technology involves analyzing reference imagery gathered by a camera system to determine which parts of an image frame offer high probabilities of—relative to other image parts—containing decodable watermark data. Another aspect of the present technology whittles-down such determined image frame parts based on detected content (e.g., a cereal box) vs expected background within such determined image frame parts.