In July, our US Boston-based business team will expand with a new application and product support engineer. After three months of training at Adimec’s headquarters in Eindhoven, Netherlands, he has gained deep knowledge by studying our manuals, application notes, and collaborating with his Dutch colleagues. To further enhance his expertise, he also read several of our blog posts. Finding the most valuable ones, we’ve compiled them here for you to accelerate your learning curve into the vision world!

These blogs are organized around three key themes: data transport, flat field correction, and noise & dynamic range. By exploring these topics through the linked articles below, you’ll quickly grasp essential concepts in machine vision.

Theme 1: Image Data Transport – From Pixel to PC via CoaXpress

Understanding how data moves from camera sensors to processing systems is critical for any vision application. While frame grabbers and cameras are often treated as a single unit, troubleshooting requires examining each component individually—especially when addressing data rate issues related to sensor, camera, or frame grabber interfaces.

For an in-depth exploration of this topic:

Theme 2: Flat Field Correction – Achieving Uniform Image Quality

A camera that produces consistent, artifact-free images is a top priority for system engineers. This theme covers various flat field correction techniques and their practical implications—equipping you with the knowledge to choose the right approach for high-resolution applications.

For detailed insights into this topic:

Theme 3: Noise and Dynamic Range – Evaluating Camera Performance

Dynamic range, signal-to-noise ratio (SNR), and read noise are key metrics for assessing camera performance. Learn how to interpret these specifications and determine which camera best suits your needs for detecting faint signals in complex imaging scenarios.

For a deeper dive into this topic:

Last Updated: 2025-09-04 21:17:53