Vehicle Image Clarity via Threshold Processing
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Solution Overview
Problem
Current vehicle camera monitoring systems (CMS) face issues with image clarity due to dirt or debris, leading to inadequate object detection and classification, and existing solutions often require manual cleaning without automated assistance.
Innovation Solution
An image detection and classification system that uses a novel feature descriptor combining the 'what' and 'where' of features, employing Fourier Fans to improve image clarity and object detection efficiency, and includes automated alerts and control systems to mitigate hazards.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If image processing is performed to improve clarity when obstruction exceeds threshold, then image clarity is improved, but processing time and computational resources increase
Solution Approach 1:
The system applies image processing selectively rather than continuously - only when obstruction detection exceeds a predetermined threshold. This partial action approach improves image clarity only when necessary, avoiding unnecessary processing time and computational resource consumption during clear conditions.
Solution Approach 2:
The system dynamically changes processing parameters based on obstruction levels. When obstruction is detected exceeding the threshold, the system activates enhanced processing modes with adjusted parameters to improve clarity. When obstruction is below threshold, processing parameters are reduced or deactivated, optimizing the balance between image quality and processing efficiency.
2Ease of repair
If automated cleaning devices are implemented, then system maintenance ease is improved, but device complexity increases
Solution Approach 1:
The system implements automated cleaning functionality that operates autonomously without requiring manual intervention. The cleaning device is integrated into the camera system and automatically activates when obstruction is detected, allowing the system to clean itself and maintain operational readiness without external assistance.
Solution Approach 2:
The system replaces manual cleaning operations with an automated mechanical cleaning device. This substitution eliminates the need for manual intervention while providing consistent, reliable cleaning functionality. The automated device uses mechanical means to remove obstructions from the camera lens or sensor surface.
3Measurement precision
If new feature descriptors are used for object detection, then detection accuracy is improved, but computational complexity increases
Solution Approach 1:
The system changes the parameters and characteristics of feature descriptors used in object detection. By utilizing enhanced feature descriptors with additional dimensions or different mathematical formulations, the system achieves improved detection accuracy. These parameter changes enable more discriminative feature representation while managing computational complexity through optimized algorithms.
Data Source
AI summary
A image detection and classification system for a vehicle includes a first display, a second display, an image capturing unit for capturing an image and displaying the image on at least one of the first display and the second display, and an image processing unit configured to process the captured image to improve a clarity of the captured image in response to the captured image having an obstruction value exceeding a threshold obstruction value. A method for operation of the image detection and classification system is also described.