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PowerPhotonic Ltd. - Bessel Beam Generator LB 6/24
Photonics Dictionary

machine vision software

Machine vision software is a type of software used in industrial and manufacturing settings to analyze and interpret images captured by cameras and other visual sensors. This software is a key component of machine vision systems, enabling automated inspection, measurement, identification, and guidance tasks.

Function: Machine vision software processes visual data to perform tasks such as object detection, pattern recognition, defect detection, and quality control. It automates visual inspection processes that would traditionally require human intervention.

Common components:

Image acquisition: Interfaces with cameras and sensors to capture images or video streams in real-time.

Image processing: Utilizes algorithms to enhance, filter, and segment the captured images to prepare them for analysis.

Feature extraction: Identifies and extracts important features or patterns from the processed images, such as edges, shapes, colors, and textures.

Analysis and decision-making: Applies machine learning or rule-based algorithms to analyze the extracted features and make decisions based on predefined criteria, such as pass/fail inspection, object recognition, or alignment corrections.

Communication: Interfaces with other systems or machinery to relay the results of the analysis, triggering actions like rejecting a defective product or adjusting a robotic arm's position.

Applications:

Quality control: Automated inspection of products on a production line to detect defects, ensuring consistency and quality.

Guidance: Assisting robotic systems in precise alignment, positioning, and assembly tasks.

Identification: Reading barcodes, QR codes, or text (Optical Character Recognition, OCR) for sorting or tracking products.

Measurement: Accurate measurement of dimensions, angles, and distances within an image, used in manufacturing processes.

Machine vision software increases efficiency, accuracy, and consistency in manufacturing and industrial processes. It reduces human error, speeds up production, and enables real-time decision-making, leading to improved product quality and reduced operational costs.


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