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PGSCZ


Course: The Methods and Systems of Num. Process.

Department/Abbreviation: KEF/PGSCZ

Year: 2020

Guarantee: 'doc. Ing. Luděk Bartoněk, Ph.D.'

Annotation: Centre of gravity object they are choice methods of digital image processing and their implementation on digital computer. Image format, compression, geometric transformation, morphological transformation, frequency analysis, detection edging and picture sharpening, automata and grammar at exercise of the recognition picture, neuronal nets.

Course review:
1.Relation of numerical image processing to related discipline, view, type, partition 2.Image sensors, types, properties, interface of cameras (analog, digital), picture transmission, image format, 3.Image compression (suppression redundancy information), compression descriptor JPEG 2000, confrontation of the methods unprofitable and lossless, DCT image compression, two dimensional DWT picture compression, implementation.4.Image processing - neighbors, point surroundings , distance, way, continuous area, inside and outward areas limits , surface and perimeter areas 5.Descriptive statistics - picture histogram , cum. Histogram, basic operation above visual array, brightness correction, transformation of brightness, scale, ekvalizace histogram, logical operation with imagery, picture, diffusion, filter, convolution nut.6.Method mathematical morphology, axiom and exploitation for in face of-processing picture - suppression murmur,7.Methods for spectral image processing. Discreet base function, common disk Fourier transform (DFT), FFT with reduction time, vibrational number, algorithm, programme, inverse DFT. Function FFT 2D at analyses visual nut.8.Methods of recognition. Description region in picture, show and description limits of region, analysis of geometric forms (surface, centre of gravity, chief central moment, examples of distance measurement of surface and Angles.9.Symptomatic methods of recognition. Symptomatic description of plane object - common principles, images moment, correlation, recognition of 2-D object. Discriminating function, criterion minimum of distance, minimum mistakes, parametric method of valuation, burst analysis.10. Structural method of recognition, election primitives, description of formal languages, automata, parsing. 11.Neuron nets. Using neuron nets for evaluation picture classifiers.