Lensless Near-Contact Imaging for Wide-Field Microassembly Feedback
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Solution Overview
Problem
Current machine vision systems face a tradeoff between optical resolution and field of view, limiting their ability to efficiently inspect micro-objects and microscale devices over large areas, which is crucial for microassembly processes in displays with increasing pixel counts.
Innovation Solution
A machine vision system utilizing high pixel count large format sensors and lensless near-contact image-capture modules (LNCIMs) captures diffraction patterns of micro-objects over a large field-of-view region, enhanced by grayscale and super-resolution image processing, enabling high-resolution image stitching and feedback for microassembly.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional optics with lenses are used to focus micro-objects onto a pixelated sensor, then optical resolution can be achieved, but the field of view is limited due to aberrations and space-bandwidth product constraints
Solution Approach 1:
The patent removes the lens component from the imaging system entirely, extracting the focusing function and replacing it with computational methods. This eliminates the fundamental tradeoff between resolution and field of view that lens-based systems face, as the lens is the source of the limitation.
Solution Approach 2:
The patent replaces the mechanical/optical focusing system (lenses) with a computational approach using a pixelated sensor and image processing algorithms. The physical lens is substituted with digital signal processing that reconstructs images from diffraction patterns, thereby overcoming optical aberrations and space-bandwidth product limitations.
2Measurement precision
If high-resolution image capture is performed over small increments of a large working area, then optical resolution is maintained, but the overall amount of time required for micro-assembly process significantly increases
Solution Approach 1:
The patent segments the large working area into multiple smaller fields of view that can be captured simultaneously by the extended pixelated sensor array. This allows parallel acquisition of multiple regions, reducing the total time required to image the entire working area while maintaining high resolution through computational reconstruction.
Solution Approach 2:
The patent extends the imaging system in the spatial dimension by using a large-format pixelated sensor array with multiple independently controllable regions. This dimensional expansion allows simultaneous capture of multiple fields of view across the large working area, transforming a sequential imaging process into a parallel one and thereby reducing total imaging time.
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 high-resolution imaging over a large area, improving the efficiency and effectiveness of microassembly processes by accurately positioning and orienting micro-objects and devices like micro-LEDs on a planar surface.
Implementation Method 1
capture images of diffraction patterns of micro-objects disposed on a planar working surface
Data Source
AI summary
A machine vision system and method use lensless near-contact imaging with coherent illumination, or incoherent illumination, and high pixel count large format sensors (e.g., equivalent to at least 20 to 65 mega-pixels) to produce diffraction patterns of the micro-objects or the gray scale images of the micro-objects over a large overall field-of-view of the machine vision system. The machine vision system provides feedback to a microassembler system to position, orient, and assemble microscale devices like micro-LEDs over large working areas. The effective resolution of the machine vision system can be further improved through the use of gray scale and super-resolution image processing techniques.