455-0102/01 – Digital image processing and analysis (DZO)
Gurantor department | Department of Measurement and Control | Credits | 4 |
Subject guarantor | Ing. Blanka Filipová, Ph.D. | Subject version guarantor | Ing. Blanka Filipová, Ph.D. |
Study level | undergraduate or graduate | Requirement | Choice-compulsory |
Year | | Semester | winter |
| | Study language | Czech |
Year of introduction | 2002/2003 | Year of cancellation | 2002/2003 |
Intended for the faculties | FEI | Intended for study types | Master |
Subject aims expressed by acquired skills and competences
The goal of the subject is to acquiant the students with the foundations of digital image processing and analysis.
Teaching methods
Summary
The goal of the subject is to acquiant the students with the foundations of digital image processing and analysis.
The following topics are discussed: Mathematical preliminaries of digital image processing, sampling of image signals, geometrical transformations, transformations of brightness, compression of images and image sequences, filtering, image segmentation, and pattern recognition based on classification.
Compulsory literature:
Recommended literature:
Way of continuous check of knowledge in the course of semester
Conditions for credit:
The tasks that form the content of the exercises must be carried out.
E-learning
Other requirements
Prerequisities
Subject has no prerequisities.
Co-requisities
Subject has no co-requisities.
Subject syllabus:
Lectures:
Digitizing. Properties of digital image. Metric and
topologist properties of image.
Geometrical transformations of images. Morphing and warping.
Transformations of brightness. Gamma correction. Histogram equalisation.
Image transforms. The Fourier transform, discrete Fourier transform, cosine transform.
Properties of Fourier transform and its application in digital image processing. Fast Fourier transform. Modifying the frequency spectrum of images.
Detecting edges in images. Gradient, and zero-crossing methods.
Thresholding. Optimal threshold selection. Segmentation based on region growing/splitting.
JPEG compression of images, MPEG compression of image sequences.
Sampling and reconstructing images. Aliasing.
Measuring objects. Selection and computation of features for pattern recognition. Evaluation of efficiency and optimization of set of features.
Classification and classificators. Discriminant functions and etalons. Neuron nets.
Probablistic approach to determining the discriminant functions.
Kalman filter.CCD camera.
Final test.
Computer labs:
During the exercises, the students work out a series of practical tasks (convolution, Fourier transform, compression, transformations of brightness, geometrical transformations, measuring objects, and classification). The tasks are prepared in the form of templates (pre-prepared programs) into which the sudents fill their own source code. In this way, they can focus on substantial and interesting issues. Furthermore, examples of comercially available systems for digital image processing are presented.
Conditions for subject completion
Occurrence in study plans
Occurrence in special blocks
Assessment of instruction
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