Camera Array for Harsh Environment Imaging
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Solution Overview
Problem
Existing imaging technologies are limited in their ability to operate effectively in uncontrolled or harsh environments, such as those with varying lighting conditions, shadows, reflections, occlusions, and moving objects, which hinders applications like face recognition at vehicle checkpoints.
Innovation Solution
A camera array system that employs exposure diversity, polarization diversity, spectral diversity, and spatial diversity to collect and fuse images, using preprocessing and registration techniques to enhance image quality, and incorporates active illumination and deep neural networks for face detection and recognition.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a single camera is used for imaging, then the device complexity is low, but the image quality in harsh environments deteriorates due to limited ability to handle varying lighting, shadows, reflections, and occlusions
Solution Approach 1:
The imaging system is divided into multiple camera units, each capturing different aspects of the scene (exposure diversity, polarization diversity, spectral diversity). This segmentation allows each camera to specialize in handling specific environmental impairments while the combined output provides comprehensive image quality across all conditions.
Solution Approach 2:
Multiple camera arrays with different diversity characteristics are merged into a single integrated system. The camera array includes exposure diversity cameras, polarization diversity cameras, spectral diversity cameras, and spatial diversity cameras, all working together to overcome the limitations of any single camera in harsh environments.
2Adaptability or versatility
If multiple camera arrays with diversity are used to improve image quality, then the imaging capability in harsh environments improves, but the device complexity and processing requirements increase
Solution Approach 1:
The camera array system is designed with multi-functionality, where different camera types within the array can handle various environmental challenges. The same array can address lighting variations, reflections, shadows, and occlusions by activating appropriate camera subsets, making the system universally applicable to diverse harsh environment scenarios without requiring separate specialized systems for each condition.
3Loss of information
If raw images from multiple camera arrays are processed and fused, then the image quality and information content improve, but the processing time and computational resources increase
Solution Approach 1:
The system performs preliminary actions by capturing multiple diverse images simultaneously from different camera arrays before the actual fusion processing is needed. This parallel acquisition of exposure diversity, polarization diversity, spectral diversity, and spatial diversity images allows the computational fusion to be performed more efficiently afterward, as the data is already prepared in the required formats.
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 mitigates environmental impairments to produce high-quality fused images, enabling accurate face detection and recognition even in challenging conditions, such as through windows of moving vehicles.
Implementation Method 1
Cameras of the first group are configured to collect light with exposure diversity
Implementation Method 2
Cameras of the second group are configured to collect light with polarization diversity
Implementation Method 3
The pulsed light source can be an infrared source, and at least one of the cameras can be configured to collect a portion of the infrared light
Data Source
AI summary
Methods and apparatus are disclosed for producing high quality images in uncontrolled or impaired environments. In some examples of the disclosed technology, groups of cameras for high dynamic range (HDR), polarization diversity, and optional other diversity modes are arranged to concurrently image a common scene. For example, in a vehicle checkpoint application, HDR provides discernment of dark objects inside a vehicle, while polarization diversity aids in rejecting glare. Spectral diversity, infrared imaging, and active illumination can be applied for better imaging through a windshield. Preprocessed single-camera images are registered and fused. Faces or other features of interest can be detected in the fused image and identified in a library. Impairments can include weather, insufficient or interfering lighting, shadows, reflections, window glass, occlusions, or moving objects.