Clave: 22A8029
No. de horas: 72
Créditos: 5
Tipo de asignatura: Optativa
Fecha de elaboración: 2022-01-20
Objetivo general:
The student will learn formal concepts related to image analysis that help him or her to understand different techniques of this domain. The student will also be able to implement variousimage processing techniques to solve problems related to image analysissuch as segmentation, characterization, enhancement among others.
Temas:
mage formation(8hours)I.I PerspectiveprojectionI.II DigitizationI.III QuantizationII.Image characterization(16hours)II.I Mathematical characterizationII.II Superposition and convolutionII.III Transform domain processingIII.Image statistics and texture (16 hours)III.I Random variablesIII.II Correlation and spectraIII.III Invariant texture featuresIII.IV Variant texture featuresIV.Image analysis and enhancement(16hours)IV.I Noise suppression IV.II Brightness and contrast adjustment IV.III Histogram equalization IV.IV Edge and contour detection V. Image segmentation (16 hours)V.I Amplitud segmentationV.II Clustering segmentationV.III Region-basedSegmentationV.IV Boundary segmentationV.V Segment Labeling
Bibliografía:
Bolón-Canedo, V., Remeseiro, B. Feature selection in image analysis: a survey. Artif Intell Rev 53, 2905–2931 (2020)https://doi.org/10.1007/s10462-019-09750-3[4] Mahdieh Poostchi, Kamolrat Silamut, Richard J. Maude, Stefan Jaeger, George Thoma, Image analysis and machine learning for detecting malaria, Translational Research, Volume 194,2018, https://doi.org/10.1016/j.trsl.2017.12.004