Retroreflective Object Location Using Image Subtraction
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Solution Overview
Problem
In situations with strong ambient light or when retroreflective materials are damaged or soiled, it becomes challenging to locate retroreflective objects and identify their features in digital images, as the retroreflective properties are not as conspicuous compared to the surrounding scene.
Innovation Solution
A system and method that involve acquiring multiple digital images - one with light emitted from an illuminator and another without or with less light - to generate a compound image by subtracting the second image from the first, which aligns the content and enhances the visibility of retroreflective objects by reducing ambient light, thereby making them more conspicuous.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple images are acquired and processed to generate a compound image, then the visibility of retroreflective objects is improved, but the device complexity and processing time increase
Solution Approach 1:
The system segments the image acquisition process into multiple separate acquisitions - one with illuminator light and one without - to isolate the retroreflective signal from ambient light interference. This segmentation allows selective processing of specific light components to enhance retroreflective object visibility.
Solution Approach 2:
The system adds a temporal dimension by acquiring images at different times (with and without illuminator activation) and combines them through image subtraction. This dimensional approach separates retroreflective signals from ambient background light, improving detection capability.
2Measurement precision
If multiple images are acquired and processed to generate a compound image, then the visibility of retroreflective objects is improved, but the time required for object location increases
Solution Approach 1:
The system performs preliminary image acquisition with and without illuminator light before final object location processing. By pre-acquiring these reference images and performing subtraction to create a compound image, the system prepares enhanced data that speeds up subsequent retroreflective object detection and location.
Solution Approach 2:
The system creates a compound image as a processed copy that emphasizes retroreflective features by subtracting ambient light components. This copied enhanced image serves as an optimized input for faster and more accurate object location compared to processing raw individual images.
3Measurement precision
If content alignment is performed before generating the compound image, then the accuracy of object location is improved, but the processing complexity increases
Solution Approach 1:
The system performs content alignment as a preliminary step before generating the compound image through subtraction. By aligning the illuminator image and non-illuminator image beforehand, the system ensures that corresponding features match, which is essential for accurate retroreflective object location in the final compound image.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach improves the ability to locate and identify retroreflective objects, especially in bright conditions or when the retroreflective material is damaged, by creating a compound image that highlights the retroreflective object more clearly than the surrounding scene, facilitating better recognition and feature identification.
Implementation Method 1
A retroreflective material is a material that reflects light back to its source with a minimum of scattering
Data Source
AI summary
Systems and methods are disclosed for locating a retroreflective object in a digital image and/or identifying a feature of the retroreflective object in the digital image. In certain environmental conditions, e.g. on a sunny day, or when the retroreflective material is damaged or soiled, it may be more challenging to locate the retroreflective object in the digital image and/or to identify a feature of the object in the digital image. The systems and methods disclosed herein may be particularly suited for object location and/or feature identification in situations in which there is a strong source of ambient light (e.g. on a sunny day) and/or when the retroreflective material on the object is damaged or soiled.