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B&R introduces new vision functions for enhanced image processing

B&R’s latest vision functions offer increased flexibility and productivity for automation applications

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B&R Industrial Automation has unveiled a suite of new vision functions designed to enhance image processing capabilities in automation systems. The new functions, available for both vision sensors and smart cameras, simplify the integration of advanced vision technology into machine applications. 

Key features include the Simple Matching function for training images with fewer arguments, the Clutter Matching function to manage clutter in pick-and-place tasks, and the Calibration function to correct perspective errors. Additionally, the Image Manipulation function allows for applying filters to read curved fonts, while the Simple Logic & Mathematics function enables direct use of vision results for controlling subsequent processing steps. These updates aim to boost productivity and flexibility in automation settings.

The new vision functions provide automation programmers with an intuitive interface to configure advanced vision features, encapsulating complex HALCON program code for easier use. The Simple Matching function simplifies image training by reducing the number of arguments required, offering an alternative to traditional edge-based matching algorithms. The Clutter Matching function defines areas around a matching target where no clutter is allowed, which is crucial for accurate pick-and-place operations. The Calibration function corrects perspective or optical distortions, converting pixel values into metric measurements necessary for precise analysis and subpixel range measurements. The Image Manipulation function applies filters and other manipulations to images, aiding in tasks such as reading curved fonts. Finally, the Simple Logic & Mathematics function leverages intermediate results from vision functions to manage subsequent image processing steps directly on the camera.

These new functionalities are set to enhance the flexibility and productivity of image processing in automation applications, offering improved performance and ease of integration into existing systems.

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