LabVIEW for Computer Vision and Image Processing: Build Vision Apps

Visual inspection and automated imaging are critical in modern manufacturing, robotics, and research. Acquiring the skills to process digital images and extract meaningful data using LabVIEW opens up powerful opportunities in industrial automation. This text-based course guides you through the core concepts of computer vision and image processing. You will transition from understanding how digital images are represented in memory to designing functional vision applications that can detect shapes, track objects, and read barcodes. What you'll learn: - Understand the fundamentals of digital images, pixel formats, and spatial calibration. - Configure image acquisition workflows using modern hardware standards like GigE Vision and USB3 Vision. - Apply essential image processing algorithms, including thresholding, filtering, and edge detection. - Implement advanced feature detection techniques such as pattern matching, color analysis, and optical character recognition (OCR). - Design automated vision workflows to count objects, track moving targets, and decode barcodes. - Practice building vision-based application logic through step-by-step written exercises and block-diagram analysis. You will begin with foundational terminology, learning how images are acquired and manipulated within the LabVIEW environment. From there, the written guides take you through practical algorithms and feature extraction methods, culminating in the logical design of real-world vision applications. This course is designed for beginners, engineers, and students who want to learn computer vision using LabVIEW. No prior image processing experience is required. Start reading today and build your first automated vision application.