Hidden Image Decoding via Dynamic Edge Detection Filters
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Solution Overview
Problem
Existing hidden image decoding methods are limited by the need for specific physical lenses and foreknowledge of encoding parameters, restricting the ability to decode hidden images without access to such information.
Innovation Solution
A computer-implemented method using dynamic image processing filters, such as edge detection filters, to decode encoded hidden images without prior knowledge of encoding techniques or parameters, by iteratively adjusting filter parameters until the hidden image is revealed.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If custom physical lenses with specific frequencies are used to decode hidden images, then the decoding accuracy is improved, but the device complexity and requirement for specialized equipment increases
Solution Approach 1:
The patent replaces the mechanical/optical system of physical lenses with a digital image processing system. Instead of requiring custom physical lenses with specific frequencies, the invention uses computer-implemented methods that apply digital filters and algorithms to decoded images, eliminating the need for specialized optical equipment while maintaining decoding accuracy.
Solution Approach 2:
The patent creates a digital copy of the decoding process. Rather than using physical lenses that directly focus light, the system captures images with standard cameras and then applies digital processing algorithms to reveal hidden images, effectively copying the function of physical lenses through software-based image manipulation.
2Reliability
If foreknowledge of encoding parameters is required to decode hidden images, then the decoding reliability is improved, but the ease of operation deteriorates
Solution Approach 1:
The patent implements self-service decoding where the system automatically determines encoding parameters without requiring user input. The computer-implemented method analyzes the encoded image itself to identify and extract hidden images, eliminating the need for users to provide foreknowledge of encoding parameters while maintaining reliable decoding.
Solution Approach 2:
The patent employs feedback mechanisms where the decoding system iteratively processes images, adjusting parameters based on the analysis of encoded image characteristics. This feedback loop allows the system to adapt to different encoding methods automatically, maintaining reliability without requiring prior knowledge from the user.
3Adaptability or versatility
If multiple hidden image types with different encoding techniques are decoded, then the adaptability is improved, but the device complexity increases
Solution Approach 1:
The patent creates a universal decoding system that can handle multiple hidden image types through a single software platform. The computer-implemented method uses a comprehensive set of digital filters and algorithms that can process various encoding techniques, allowing one system to perform multiple decoding functions without requiring separate specialized equipment for each image type.
Data Source
AI summary
In one implementation, a computer-implemented method for identifying hidden features in digital images includes: detecting, by the computer system, one or more visual features in a digital image; applying one or more edge detection filters to the digital image to generate a modified digital image; detecting one or more candidate hidden features that are included in the modified digital image; comparing the one or more visual features in the digital image with the one or more candidate hidden features; determining whether a hidden image is present in the digital image based on the comparison of the one or more visual features in the digital image with the one or more candidate hidden features; and providing, by the computer system and in response to determining that a hidden image is present in the digital image, information that identifies that the hidden image has been detected.