Multi-Region Imaging Optics for Moving Object Detection
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Solution Overview
Problem
Traditional imaging systems face challenges in capturing information from moving objects due to factors like object speed, distance, orientation, and illumination, particularly when trying to achieve clear imaging over a wide range of object distances with good low light performance.
Innovation Solution
A multi-region imaging system is designed with optics that form two distinct image portions, each in focus over separate conjugate distance ranges, separated by at least 40 cm, using a sensor array and digital signal processing to generate and process image data, and adjusting shutter rates and directions to compensate for object motion.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional imaging systems use a narrow depth of field design, then image quality is high over a narrow region, but the system cannot capture objects at multiple distances simultaneously
Solution Approach 1:
The imaging system divides the object space into multiple discrete depth regions (first depth region and second depth region separated by at least 40 cm). Each region has its own optimized focus range, allowing the system to provide high-quality imaging for objects at different distances simultaneously by segmenting the overall depth range into manageable focal zones.
2Adaptability or versatility
If the imaging system increases depth of field to cover wide distance ranges, then more objects can be imaged, but image quality deteriorates across all distances
Solution Approach 1:
Each depth region is optimized with local quality principles - the first depth region has its own best focus range optimized for near objects, while the second depth region has its own best focus range optimized for far objects. This allows each region to maintain high image quality for its specific distance range rather than compromising overall quality across all distances.
3Reliability
If the shutter rate is increased to reduce motion blur of moving objects, then motion blur is reduced, but the system performance degrades due to reduced light capture
Solution Approach 1:
The system dynamically adjusts shutter rates based on the detected depth region of the object. Objects in the first depth region may use different shutter rates than objects in the second depth region. This dynamic adaptation allows the system to optimize both motion blur reduction and light capture efficiency according to the specific imaging conditions of each depth region.
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 achieves clear imaging of moving objects across a wide range of distances with improved low light performance and reduced motion blur, enabling effective data capture and processing of information from both near and far field objects.
Implementation Method 1
optics for forming an optical image that provide a first region in the optical image that is characterized by a first range of best focus and a second region in the optical image that is characterized by a second range of best focus
Implementation Method 2
A sensor array converts the optical image to a data stream
Data Source
AI summary
Systems and methods for generating images of an object having a known object velocity include imaging electromagnetic radiation from the object onto a sensor array of an imaging system, adjusting at least one of a shutter rate and a shutter direction of the imaging system in accordance with an image velocity of the image across the sensor array, and sampling output of the sensor array in accordance with the shutter rate and the shutter direction to generate the images. Systems and methods for generating images of an object moving through a scene include a first imaging system generating image data samples of the scene, a post processing system that analyzes the samples to determine when the object is present in the scene, and one or more second imaging systems triggered by the post processing system to generate one or more second image data samples of the object.