Watermark Extraction Using Distortion Prediction and Region Segmentation
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Solution Overview
Problem
Existing methods for detecting and decoding digital watermarks in digital content are inefficient and computationally expensive, particularly when dealing with distorted images, as they require full processing of content to identify watermarks, leading to resource wastage and slower identification.
Innovation Solution
The use of machine learning models, specifically an encoder and decoder pipeline trained jointly, to detect and decode watermarks by predicting distortions and modifying images to preserve the watermark, allowing for efficient extraction of embedded data without full content processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If existing methods are used to detect and decode digital watermarks, then watermark extraction can be performed, but computational resources and processing time are excessive
Solution Approach 1:
The patent segments the image processing task by first detecting watermark locations using a specialized detector, then extracting only those specific regions rather than processing the entire image. This segmentation approach allows the system to identify and process only the relevant portions containing watermarks, significantly reducing computational resources and processing time while maintaining extraction accuracy.
Solution Approach 2:
The patent extracts and isolates the watermark portions from the larger image context. By using the watermark detector to identify specific locations and then extracting only those regions for decoding, the system removes unnecessary processing of non-watermark areas. This extraction strategy enables fast and robust watermark recovery while minimizing computational energy consumption.
2Reliability
If full processing of content is performed to identify watermarks, then accurate watermark detection is achieved, but resource wastage increases
Solution Approach 1:
The patent performs preliminary detection of watermark locations before extraction. The watermark detector analyzes the image to identify regions containing watermarks, and only those specific regions are then extracted for decoding. This preliminary action ensures that computational energy is not wasted processing areas without watermarks, while maintaining detection accuracy by focusing resources only where needed.
Solution Approach 2:
The patent applies different processing quality to different regions of the image. Instead of uniformly processing the entire image, the system applies high-quality extraction only to local regions identified as containing watermarks. This local quality approach maintains detection accuracy for watermarked areas while reducing overall computational energy consumption by avoiding unnecessary processing of non-watermark regions.
3Reliability
If distortion detection and image modification are performed, then watermark preservation is improved, but processing complexity increases
Solution Approach 1:
The patent implements a feedback mechanism where the distortion detector analyzes the extracted watermark region and provides information about applicable distortions. Based on this feedback, the system selectively applies only the necessary distortion corrections to the extracted portion. This feedback-driven approach improves watermark preservation by addressing actual distortions present while avoiding unnecessary processing steps, thus managing complexity effectively.
Solution Approach 2:
The patent applies partial distortion correction by identifying and correcting only the specific distortions detected in the watermark region, rather than applying comprehensive processing to all possible distortion types. This partial action strategy improves watermark preservation for the actual distortions present while avoiding the complexity of handling all potential distortion scenarios, achieving a balance between reliability and processing complexity.
Data Source
AI summary
Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for generating and decoding watermarks. An image and a data item is received. The encoder generates a first watermark and then a second watermark is generated using multiple first watermarks. The second watermark is used to watermark the image by overlaying the second watermark over the image. To decode the watermark, presence of a watermark is determined on a portion of an image. A distortion model determines distortions in the image and modifies the portion of the image based on the predicted distortions. The modified portion is decoded using the decoder to obtain a predicted first data item that is further used to validate the watermark based on the first data item.