Vehicle Control System Image Sensor Dynamic Range
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Solution Overview
Problem
Conventional object detection techniques using in-vehicle cameras face challenges with high contrast images due to insufficient dynamic range, leading to overexposure or underexposure areas, which can result in missed object detection and erroneous identification of objects.
Innovation Solution
A vehicle control system employing a light-receiving section with multiple filters and light-receiving elements generates discrete image data for each filter, allowing for accurate object detection by combining high-sensitivity and low-sensitivity image data, thereby addressing dynamic range issues and preventing positional offset errors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a single image is captured by a camera with insufficient dynamic range, then the image acquisition is simple and fast, but overexposure or underexposure areas occur which prevent accurate object detection
Solution Approach 1:
The image sensor is divided into multiple light-receiving sections, each equipped with different filters (e.g., red, green, blue, infrared) to capture images in different wavelength bands simultaneously. This segmentation allows each section to optimize for specific lighting conditions, preventing overexposure and underexposure while maintaining detection accuracy across diverse scene conditions.
2Measurement precision
If multiple images are acquired at different time points to handle dynamic range, then object detection coverage improves, but determination of identical objects across images becomes time-consuming and error-prone
Solution Approach 1:
Multiple light-receiving sections capture images of different wavelength bands simultaneously in a single exposure event, rather than sequentially over time. This preliminary action of capturing all necessary spectral information at once eliminates the need for time-consuming object matching across multiple time points, while still providing comprehensive dynamic range coverage.
3Measurement precision
If multiple images are acquired at different time points, then comprehensive object detection is possible, but single objects may be erroneously detected as multiple different objects
Solution Approach 1:
The system segments the detection task by using different wavelength bands to detect different types of objects or different aspects of the same object. By processing these segmented detections and fusing the results, the system maintains high reliability and avoids erroneous duplicate detections that would occur with temporal multi-image acquisition.
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
The system effectively detects objects in high-contrast scenes without omission, improving accuracy by using discrete image data to handle overexposure and underexposure areas simultaneously, ensuring correct identification of objects and reducing erroneous detections.
Implementation Method 1
a light-receiving section which has a plurality of filters having different pass bands, and a plurality of light-receiving elements, each of which receives incident light via any one of the filters
Implementation Method 2
a plurality of light-receiving elements, each of which receives incident light via any one of the filters
Data Source
AI summary
A vehicle control system includes a light-receiving section which has a plurality of filters having different pass bands, and a plurality of light-receiving elements, each of which receives incident light via any one of the filters; an image data generation section which, when receiving general image data which is an output of the light-receiving section, extracts outputs of the light-receiving elements correlated to the filters to generate discrete image data, which is image data for each of the filters; an image data processing section which detects at least one object, based on the discrete image data generated by the image data generation section or composite image data generated by combining the discrete image data; and a vehicle control section which performs vehicle control, according to the object detected by the image data processing section.