Course Instructor: Francisc Iacob

Syllabus:

After the introductory presentation of the file formats and data structures for image analysis the course discuss a number of topics related to signal sampling and transformations (Fourier, Walsh, Hadamard, cosine, Haar, wavelets, etc.).

In the chapter "Image enhancements" are studied statistical values, extending contrast, histogram modification techniques, increasing image clarity. For image filtering are considered methods in frequency domain and space domain.

To restore images noise models are discussed and further filtering solutions in the spatial domain and the frequency domain. An important section of the course is represented by operations on images: arithmetic operations, operations based on convolution, derivative-based operations, morphological operations, including basic morphological algorithms (border extraction, region fill, extraction of connected components, convex hull, thinning, thickening, skeletons, pruning) and morphological operations on images with gray levels (dilation, erosion, opening, closing, morphological smoothing, morphological gradient, "top-hat" transformation, textural segmentation, granulometry).

The chapter "Segmentation techniques" approaches the threshold techniques, contour detection based on Laplace, Roberts, Prewitt, Sobel, Canny, Hough operators, including region based segmentation.

The last chapter refers to the numerical systems for image processing (massive processors, systolic systems, pipeline systems, MIMD systems with distributed memory and shared memory, imaging systems connected to PC).