Computer Vision Basics: Image Processing and Feature Detection

Related lectures (28)

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Explores image processing techniques such as contrast manipulation, enhancement, and sharpening using Fiji software.

Provides an overview of image formation and transformation principles in computer vision.

Covers techniques for reconstructing color images using optical detection and artificial intelligence to enhance image quality and reduce noise.

Explores directional image analysis and the implementation of steerable filters for edge and ridge detection.

Covers the techniques for recovering 3D shape information from 2D images using shading models and modern deep learning approaches.

Covers image processing techniques including noise addition, filtering, and image enhancement using various filters and tools.

Covers edge detection, texture analysis, Canny's algorithm, filterbanks, and segmentation techniques.

Covers image smoothing, noise reduction, and segmentation techniques using filters and transforms.

Explores classic image filters like Moving Average, Gaussian Blur, Sobel filter, and Laplacian operator.

Covers the basics of image processing for microscopy, including acquiring, correcting defects, enhancing images, and extracting information.