Toothbrush Camera Image Processing for Bristle Occlusion Removal
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Solution Overview
Problem
Existing imaging technologies for devices such as cameras are facing challenges in the field of physical devices and mechanical devices, specifically cameras are facing challenges in the personal care sector, specifically electric tooth brushes with integrated cameras, where the presence of bristles results in interference and occlusion within the camera images, leading to algorithmic complications in image processing.
Innovation Solution
An image processing system for personal care devices, such as toothbrushes, that processes images to remove cleaning elements like bristles from the background, using a processor to generate a background image with moving parts removed, employing methods like median filters, optical flow, independent component analysis, and morphological operations to improve image quality and simplify subsequent processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a camera is integrated into the head of an electric toothbrush to capture images for diagnostics and location sensing, then image-based diagnostic capability and location sensing accuracy are improved, but the bristles create interference and occlusion in the captured images
Solution Approach 1:
The patent extracts and removes the harmful bristle elements from the captured images through image processing algorithms. The system identifies bristle regions and excludes them from the final image output, effectively separating the useful diagnostic information from the harmful occlusion caused by bristles.
Solution Approach 2:
The patent introduces an intermediary image processing system that acts as a mediator between the camera capture and the final diagnostic output. This intermediary layer processes the raw images to remove bristle interference, allowing the camera to remain in its integrated position without compromising image quality.
2Object-affected harmful factors
If the camera and optics are adapted to minimize obstruction for specific bristle characteristics, then image quality is improved, but the device complexity and manufacturing cost increase due to customization requirements
Solution Approach 1:
The patent creates a universal image processing solution that works with various bristle types and configurations without requiring custom optical adaptations. The algorithmic approach to bristle removal is applicable across different toothbrush head designs, making the system multi-functional and adaptable without increasing hardware complexity.
Solution Approach 2:
The patent replaces the mechanical/optical approach to minimizing bristle obstruction with an algorithmic/image processing approach. Instead of physically adapting the optics for each bristle configuration, the system uses computational methods to remove bristle interference, substituting mechanical customization with software-based universal processing.
3Measurement precision
If images are processed to remove moving bristles and generate clean background images, then diagnostic information quality is improved, but data processing time and computational resources increase
Solution Approach 1:
The patent performs preliminary identification and segmentation of bristle regions in the image processing pipeline. By pre-identifying bristle locations and characteristics before the main diagnostic analysis, the system prepares the data in advance, reducing the computational burden during subsequent processing stages and optimizing overall processing time.
Data Source
AI summary
Images received from an imaging device mounted at a head of a personal care device are processed. Cleaning elements of the personal care device are visible in at least one of the images. The images are processed to generate a background image with moving parts in the sequence of images removed such that the cleaning elements of the personal care device are removed from the background image. This image provides improved image quality, with occlusion resulting from the cleaning elements addressed. This simplifies subsequent image processing. for example for caries and plaque detection.