Computer Vision Fundamentals Course – Image Processing, Filtering & Edge Detection
عدد الدروس : 129 عدد ساعات الدورة : 65:07:43 شهادة معتمدة : نعم التسجيل في الدورة للحصول على شهادةللحصول على شهادة
- 1- التسجيل
- 2- مشاهدة الكورس كاملا
- 3- متابعة نسبة اكتمال الكورس تدريجيا
- 4- بعد الانتهاء تظهر الشهادة في الملف الشخصي الخاص بك
قائمة الدروس
عن الدورة
This Computer Vision Fundamentals course provides a solid foundation in classical image processing and early-stage computer vision techniques. It is designed to help you understand how images are represented, processed, and analyzed before applying modern deep learning methods.
You will begin with an introduction and historical overview of computer vision, followed by a deep explanation of image formation and how digital images are created from real-world scenes.
Next, you will study image representation techniques, including how images are stored and processed in computers. The course then introduces linear filtering, which is essential for smoothing, sharpening, and enhancing images.
You will also explore frequency domain analysis, learning how images can be transformed and processed in different mathematical spaces. Image sampling concepts are covered to help you understand resolution and digital reconstruction.
A major part of the course focuses on edge detection, which is used to identify boundaries and shapes within images. You will then move into feature detection, including blobs and corners, which are important for object recognition and tracking.
Finally, the course introduces scale-space theory, image pyramids, and filter banks, which are advanced tools for multi-scale image analysis.
By the end of this course, you will have a strong understanding of classical computer vision techniques that form the basis of modern AI vision systems.
