Optimizing Vision Systems - Strategies for Leveraging FPGA-based Preprocessing
In this on-demand webinar, our vision expert walks you through a performance comparison between FPGA, CPU, and GPU, and share key considerations for real-world deployment. Gain insights you can apply directly to your manufacturing environment—whether you're evaluating architectures or optimizing existing systems.
Are you facing these challenges?
One of the biggest issues in modern machine vision is the ability to process large volumes of data in real time, especially from high-resolution cameras. Traditional CPU- and GPU-based architectures are no longer sufficient to handle the increasing data throughput and algorithmic complexity.
If you are building or operating a high-performance machine vision system and encountering any of the following challenges, this webinar will provide practical solutions to address your pain points.
Data Throughput Limitations With the introduction of high-resolution sensors, data volume increases rapidly—often beyond what existing systems can manage.
Excessive System Costs Systems built around expensive GPUs and high-performance CPUs increases burden on hardware costs.
Decreased Productivity Delays in real-time processing can slow down production lines and reduce inspection accuracy.
Increased system complexity Complex image preprocessing can degrade overall system performance and make system management more difficult.
In image processing, the biggest challenge is no longer the algorithm. The success of a vision system now hinges on having the right architecture to efficiently handle massive data volumes.
Who should watch this webinar?
This webinar is especially valuable for vision system designers, machine vision engineers, and process automation managers who need to strike the right balance between system performance and cost efficiency. While FPGAs are often avoided due to their traditionally complex development process, tools like VisualApplets now make it possible to unlock powerful performance gains—without requiring deep FPGA expertise. In this session, we will share practical optimization strategies to help you maximize performance while minimizing costs
Webinar Highlights
Overview of machine vision architectures: CPU, GPU, and FPGA
Guide to implementing and optimizing image processing
Easy FPGA development with VisualApplets
Real-world examples of industrial deployment
Watch the free webinar
Björn Rudde
Vision Systems Consultant
Björn Rudde is a vision system expert with over 15 years of experience in developing high-performance image processing systems. He has been with Basler AG for the past 10 years, successfully leading vision system optimization projects for manufacturing companies around the world. Björn is widely recognized for his deep expertise in FPGA-based image preprocessing and for leveraging VisualApplets to maximize system performance in demanding industrial applications.