ROI Tags for Precise Moving-Object Image Masking
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Solution Overview
Problem
Existing technologies for finding regions of interest (ROI) in images of moving objects are inadequate, particularly in terms of precise control over size, position, and orientation, and do not adequately address privacy masking needs, often relying on accurate distance measurement.
Innovation Solution
A method and device for locating a ROI in an image by searching for a tag with a predefined format that codes ROI information, including size and relative position indications, allowing for precise determination of the ROI's size and position relative to the tag's size and position, and a tag system comprising multiple tags with a common format.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If accurate distance measurement is used to determine ROI size, then ROI size accuracy is improved, but device complexity and measurement requirements increase
Solution Approach 1:
The patent uses a tag with a known physical size as a reference copy. The ROI size is determined by comparing the tag's image size in the captured image to its known physical size, eliminating the need for complex distance measurement devices. The tag acts as a built-in scale reference that is automatically captured along with the scene.
Solution Approach 2:
The tag contains embedded ROI information including size indications that are self-contained within the tag itself. The tag serves its own measurement function by providing reference information about its physical dimensions, allowing the system to determine ROI size without external measurement devices or complex calculations.
2Device complexity
If static ROI specification is used for stationary monitoring, then system simplicity is improved, but adaptability to moving objects deteriorates
Solution Approach 1:
The patent makes the ROI dynamic by associating it with a moving tag rather than a fixed coordinate system. As the tag moves within the scene, the ROI automatically follows the tag's position and updates accordingly. This dynamic approach maintains system simplicity while enabling tracking of moving objects through the tag's movement.
Solution Approach 2:
The patent adds the dimension of tag association to the traditional static ROI concept. Instead of defining ROI by fixed image coordinates, the ROI is defined by its relationship to the tag, creating a new dimension of reference that enables both stationary and moving object monitoring through the same mechanism.
3Adaptability or versatility
If ROI follows moving tag, then adaptability to moving objects is improved, but position control precision deteriorates
Solution Approach 1:
The patent implements feedback by continuously detecting the tag's position in each captured image and using that information to update the ROI position. The system reads the tag's current coordinates from the image, compares them to the previous position, and adjusts the ROI accordingly, maintaining precise position control while tracking moving objects.
Solution Approach 2:
The patent performs preliminary action by pre-defining the ROI size and position relationship to the tag before tracking begins. The ROI parameters are calculated in advance based on the tag's known physical dimensions and desired monitoring area, establishing a stable reference framework that maintains precision during subsequent tracking operations.
4Ease of operation
If tag-based ROI definition is used, then ease of operation is improved, but vulnerability to tag abuse increases
Solution Approach 1:
The patent applies preliminary anti-action by implementing verification mechanisms that check tag authenticity before accepting the tag as a valid ROI reference. The system verifies that the tag matches expected characteristics and has not been tampered with, preventing unauthorized or malicious tags from compromising the monitoring system.
Solution Approach 2:
The patent replaces physical tag security mechanisms with digital verification methods. Instead of relying on physical tag characteristics that can be copied, the system uses digital authentication and verification protocols to confirm tag legitimacy, making it more difficult to abuse while maintaining ease of operation.
Data Source
AI summary
A tag for indicating a region of interest, ROI, has a predefined format and codes ROI information, which is readable by imaging the tag and which includes a size indication and a relative position indication, the respective indications allowing the ROI's size and position to be determined relative to the tag's size and position. A method for locating a ROI in an image comprises: obtaining an image; searching in the image for a tag with the predefined format; and determining a ROI on the basis of the tag's size and position in the image and the ROI information. A method for generating a tag comprises: obtaining an image including a visible provisional tag of same physical size as the tag to be generated; obtaining operator input identifying a ROI in the image; deriving the size indication and relative position indication; and printing the tag.


