Dr.-Ing. Ronny Hänsch Probabilistic Image Segmentation€¦ · group adjacent pixels based on...
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Master or Diploma Thesis Probabilistic Image Segmentation Computer Vision and Remote Sensing Dr.-Ing. Ronny Hänsch Room MAR6.043 Marchstr. 23 D-10587 Berlin [email protected] Image segmentation algorithms aim to group adjacent pixels based on certain similarity criteria. The set of criteria that is used by a particular method is mostly defined ad-hoc and stays unchanged during the process of segmentation. However, in iterative image segmentation approaches such as region growing, the available information is changing over time. This change of information should have an influence on which criteria are used and how much certain features can be trusted. A. Stanski et al, „A projection and density estimation method for knowledge discovery“ The goal of this thesis is to implement a region growing method that automatically selects suitable merging criteria based on properties of the involved segments. The framework should be modelled in a probabilistic manner to allow an easy selection and evaluation of merging criteria. Keywords: Image segmentation, region growing, probability theory Involved tasks: – Literature research – Selection of suitable criteria – Implementation of a probabilistic framework for region growing (Recommended) requirements: – Good knowledge about digital image processing (e.g. attendance in lecture DIP) – Good programming skills (e.g. C++) – Good mathematical skills (e.g. probability theory, stochastic) Language: German / English
Transcript of Dr.-Ing. Ronny Hänsch Probabilistic Image Segmentation€¦ · group adjacent pixels based on...
Master or Diploma Thesis
Probabilistic Image Segmentation
Computer Vision and Remote Sensing
Dr.-Ing. Ronny Hänsch
Room MAR6.043Marchstr. 23D-10587 Berlin
Image segmentation algorithms aim togroup adjacent pixels based on certainsimilarity criteria. The set of criteriathat is used by a particular method ismostly defined ad-hoc and staysunchanged during the process ofsegmentation. However, in iterativeimage segmentation approaches such asregion growing, the availableinformation is changing over time. Thischange of information should have aninfluence on which criteria are used andhow much certain features can betrusted. A. Stanski et al, „A projection and density estimation method for knowledge discovery“
The goal of this thesis is to implement a region growing method that automatically selects suitablemerging criteria based on properties of the involved segments. The framework should be modelledin a probabilistic manner to allow an easy selection and evaluation of merging criteria.
Keywords: Image segmentation, region growing, probability theory
Involved tasks:– Literature research– Selection of suitable criteria– Implementation of a probabilistic framework for region growing
(Recommended) requirements:– Good knowledge about digital image processing (e.g. attendance in lecture DIP) – Good programming skills (e.g. C++)– Good mathematical skills (e.g. probability theory, stochastic)
Language: German / English
