Executive Development Programme in Image and Video Processing with OpenCV and Python

This course is tailored for mid-to-senior level professionals in technology, data science, and engineering who seek to enhance their skills in image and video processing. Participants will gain hands-on experience with OpenCV and Python, mastering key techniques for image and video analysis, including object detection, tracking, and machine learning integration.

Upon completion, learners will be able to implement advanced image and video processing solutions, translate business requirements into technical specifications, and lead projects involving real-time data analysis and computer vision applications.

1. 1. Introduction to Image and Video Processing: Learners will understand the basics of image and video processing, including image representation, types of images, and fundamental operations. They will gain practical skills in using Python for basic image handling and manipulation.
2. 2. Image Enhancement Techniques: This module covers various techniques to enhance the quality of images, such as contrast adjustment, histogram equalization, and noise reduction. Learners will practice applying these techniques to real-world images using OpenCV.
3. 3. Image Segmentation: Learners will explore different segmentation methods, including thresholding, clustering, and edge detection. They will implement these techniques to segment images and gain hands-on experience in preparing images for further processing.
4. 4. Object Detection with OpenCV: This module introduces learners to object detection techniques using OpenCV, focusing on pre-trained models and custom training. They will learn to detect and track objects in images and videos effectively.
5. 5. Advanced Image Filters and Transformations: Learners will delve into advanced image filtering techniques, including frequency domain processing, wavelet transforms, and morphological operations. They will apply these transformations to process and analyze complex images.
6. 6. Video Analysis and Processing: This module covers the basics of video processing, including frame extraction, video capture, and video streaming. Learners will gain skills in analyzing and processing video content for various applications.
7. 7. Tracking and Motion Analysis: Learners will study tracking algorithms and motion analysis techniques, including optical flow and Kalman filters. They will implement these methods to track objects and analyze motion in videos.
8. 8. Deep Learning for Image and Video Processing: This module introduces the use of deep learning for image and video processing, focusing on convolutional neural networks (CNNs). Learners will explore how to use deep learning models for tasks such as image classification and object recognition.
9. 9. Real-Time Image and Video Processing: Learners will learn to develop real-time image and video processing applications using OpenCV and Python. They will gain skills in optimizing algorithms for real-time performance and deploying applications on various platforms.
10. 10. Project Development and Application: In this final module, learners will apply their knowledge to develop a comprehensive project in image or video processing. They will work on a real-world problem, from project planning to implementation and deployment, integrating various skills learned throughout the programme.