“Selecting Image Sensors for Embedded Vision Applications: Three Case Studies,” a Presentation from Avnet

Monica Houston, Technical Solutions Manager at Avnet, presents the “Selecting Image Sensors for Embedded Vision Applications: Three Case Studies,” tutorial at the May 2023 Embedded Vision Summit.

Selecting the appropriate type of image sensor is essential for reliable and accurate performance of vision applications. In this talk, Houston explores some of the critical factors to consider in selecting an image sensor, including shutter type, dynamic range, resolution and chromaticity. She explores the impact of these factors through three distinct use cases: defect detection, license plate recognition and crowd counting.

For defect detection, Houston examines the advantages and disadvantages of monochrome image sensors. In license plate recognition, she highlights the importance of global shutter, pixel size, dynamic range and color space, providing a comprehensive introduction to key factors that contribute to successful recognition in varying light conditions. Lastly, she explores the trade-offs of high-resolution cameras in crowd counting applications and offers practical insights on developing fast and accurate machine learning models with high-resolution input.

See here for a PDF of the slides.

Here you’ll find a wealth of practical technical insights and expert advice to help you bring AI and visual intelligence into your products without flying blind.



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