Udemy – Fundamentals of Computer Vision 2025-4

Updated August 10, 2026 2.9 GB

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Fundamentals of Computer Vision Course. This course is a comprehensive guide to mastering digital image processing and its applications in artificial intelligence, computer vision, medical imaging, robotics, and other fields. This course provides step-by-step, hands-on, project-based training using the Python programming language and MATLAB software, and is designed for beginners to experts. The main goal is to build a solid foundation in image processing techniques and their implementation in industrial and real-world applications. Participants in this course will learn a variety of skills, including performing arithmetic and logical operations on images (such as blending, masking, and manipulation), working with linear filters (Gaussian, box, low-pass, high-pass, band-pass, and band-removal) and nonlinear filters (Laplace, unsharp masking, and smoothing). Also, topics such as image segmentation, color processing and thresholding in RGB, HSV and Lab color spaces, edge detection with Sobel, Pruitt and Kanye techniques, as well as noise reduction with median and adaptive filters are taught. Finally, practical applications of these techniques are implemented in the form of real projects such as image enhancement, object detection and pattern recognition. The complete course topics include digital image processing, OpenCV library, color thresholding, edge detection, types of filters, smoothing, blurring, sharpening, Laplace filter, object detection and tracking, color spaces and logical and arithmetic operations on images. This course is ideal for students, engineers and researchers and has no previous prerequisites and covers all the necessary concepts.