AOI CPU-GPU-FPGA Architecture for Multi-Camera Inspection
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Solution Overview
Problem
Conventional automatic optical inspection (AOI) systems based on image acquisition cards and PCs are costly, difficult to coordinate, and lack expandability, leading to poor system stability and inefficiency, making them unpopular among panel manufacturers.
Innovation Solution
An automatic optical inspection device utilizing a CPU+GPU+FPGA architecture that enables communication with multiple cameras, comprehensive control of screen lighting, and image processing, featuring an image storage unit, image computing unit, and image acquisition unit, with FPGA acting as a central controller for distributed processing and parallel image processing capabilities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If conventional image acquisition cards and PCs are used for AOI systems, then the system can perform basic image acquisition and processing, but the system becomes costly, difficult to coordinate, and lacks expandability
Solution Approach 1:
The system is divided into independent functional modules: image acquisition module with multiple camera interfaces, image processing module with GPU acceleration, control module with FPGA, and storage module. Each module operates independently with standardized interfaces, enabling easy expansion and coordination without increasing overall system complexity
Solution Approach 2:
The control module is designed with multi-functionality to handle diverse camera interfaces (Camera Link, GigE, USB3.0, CoaXPress) and multiple processing functions (image acquisition, processing, storage, transmission) through a unified architecture, eliminating the need for separate specialized hardware for each function
2Productivity
If multiple cameras are connected to improve inspection coverage, then the inspection capability is enhanced, but the data transmission burden and system complexity increase
Solution Approach 1:
The image acquisition module serves as an intermediary between multiple cameras and the processing system. It provides unified data collection and preprocessing for multiple camera inputs, managing data transmission through standardized interfaces and reducing the complexity burden on the overall system architecture
Solution Approach 2:
Multiple camera data streams are merged and processed through a unified image processing module with GPU acceleration. The system combines data from multiple cameras into a cohesive processing workflow, managing multiple data flows through a single integrated processing pipeline that reduces transmission management complexity
3Productivity
If high-speed data transmission is implemented to improve processing speed, then the image processing capability is enhanced, but the system cost and complexity increase
Solution Approach 1:
The system replaces traditional mechanical/CPU-based image processing with GPU-based parallel computing architecture. The GPU provides high-speed parallel processing capability for image data without requiring complex high-speed transmission infrastructure, achieving fast processing through computational efficiency rather than transmission speed
Solution Approach 2:
The system transitions from sequential CPU processing to parallel GPU processing, adding a dimensional aspect to computation. This architectural shift enables simultaneous processing of multiple image data streams through parallel computing cores, achieving high speed without proportionally increasing transmission complexity
Data Source
AI summary
An automatic optical inspection device, including an image storage unit; an image computing unit; and an image acquisition unit. The image storage unit includes a first communication interface and a second communication interface. The image computing unit includes a first optical interface, a second optical interface, a third optical interface, and a fourth optical interface; the image acquisition unit includes a third communication interface and a camera interface. The image storage unit is configured to transmit configuration parameters and test commands to the image computing unit, receive a test result transmitted from the image computing unit via the first communication interface, and receive data from the image acquisition unit via the second communication interface. The image computing unit is configured to receive the configuration parameters and test commands from the image storage unit, and transmit the test result to the image storage unit via the first fiber interface.