Vehicle Camera Brightness Conversion for Night Animal Detection
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Solution Overview
Problem
Current vehicle camera systems struggle to effectively recognize wild animals crossing the roadway at dusk or night due to limited field of view and inadequate illumination of regions beside the road, leading to potential collisions.
Innovation Solution
A vehicle-mounted camera system using a wide-angle or panoramic view camera combined with an artificial neural network for brightness conversion, enhancing image data to balance illumination and improve animal recognition, without additional lighting.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a narrow field of view camera is used, then animals on the roadway can be recognized, but animals approaching the road from the side cannot be detected early enough
Solution Approach 1:
The camera system is divided into multiple cameras with different fields of view: a wide-angle camera for monitoring side regions and a narrow field of view camera for monitoring the roadway. This segmentation allows each camera to specialize in detecting animals in its specific zone, solving the contradiction between early detection coverage and recognition accuracy.
2Illumination intensity
If vehicle lamps illuminate only the road region, then road visibility is sufficient, but regions next to the road remain unilluminated and animals are not visible
Solution Approach 1:
An image processing unit acts as an intermediary that takes images from the wide-angle camera covering unilluminated side regions and algorithmically enhances their brightness. This mediator compensates for the physical limitation of vehicle lamps not illuminating side regions, making animals in these areas visible without adding physical light sources.
3Loss of information
If additional lamps are installed on the sides of the vehicle to illuminate critical regions, then side region visibility improves, but design restrictions and costs increase
Solution Approach 1:
The mechanical lighting system (additional physical lamps) is replaced with an electronic/image processing system. The image processing unit algorithmically enhances the brightness of wide-angle camera images, achieving side region visibility without the mechanical complexity, design restrictions, and costs of installing additional physical lighting components.
Data Source
AI summary
There is disclosed a method and a device for avoiding accidents caused by wild animals crossing at dusk and at night by a vehicle-mounted camera system. The method for the brightness conversion of input image data of the camera into output image data includes the following steps: a) capturing input image data of a current brightness of a roadway and an adjacent region to the side of the roadway by f a vehicle-mounted camera system at dusk or at night, b) converting the input image data into output image data with a different brightness by a trained artificial neural network, and c) outputting the output image data so that the output image data can be displayed to the driver of the vehicle for the purpose of avoiding accidents involving wild animals or so that a wild animal can be recognized from the output image data by an image recognition function.