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Sub-pixel Segmentation with the Image Foresting Transform
Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Centrum för bildanalys. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Datoriserad bildanalys.
Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Centrum för bildanalys.
Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Centrum för bildanalys.
2009 (engelsk)Inngår i: Proceedings of International Workshop on Combinatorial Image Analysis: IWCIA 2009, Springer , 2009, s. 201-211Konferansepaper, Publicerat paper (Fagfellevurdert)
Fritextbeskrivning
Abstract [en]

The Image Foresting Transform (IFT) is a framework forimage partitioning, commonly used for interactive segmentation. Givenan image where a subset of the image elements (seed-points) have beenassigned user-defined labels, the IFT completes the labeling by computingminimal cost paths from all image elements to the seed-points. Eachimage element is then given the same label as the closest seed-point. Inits original form, the IFT produces crisp segmentations, i.e., each imageelement is assigned the label of exactly one seed-point. Here, we proposea modified version of the IFT that computes region boundaries withsub-pixel precision by allowing mixed labels at region boundaries. Wedemonstrate that the proposed sub-pixel IFT allows properties of thesegmented object to be measured with higher precision.

sted, utgiver, år, opplag, sider
Springer , 2009. s. 201-211
Serie
Lecture Notes in Computer Science, ISSN 0302-9743 ; 5852
Emneord [en]
Image foresting transform, Interactive image segmentation, Sub-pixel precision
HSV kategori
Forskningsprogram
Datoriserad bildanalys
Identifikatorer
URN: urn:nbn:se:uu:diva-111261DOI: 10.1007/978-3-642-10210-3_16ISBN: 978-3-642-10208-0 (tryckt)OAI: oai:DiVA.org:uu-111261DiVA, id: diva2:280148
Tilgjengelig fra: 2009-12-08 Laget: 2009-12-08 Sist oppdatert: 2018-12-02bibliografisk kontrollert
Inngår i avhandling
1. Graph-based Methods for Interactive Image Segmentation
Åpne denne publikasjonen i ny fane eller vindu >>Graph-based Methods for Interactive Image Segmentation
2011 (engelsk)Doktoravhandling, med artikler (Annet vitenskapelig)
Abstract [en]

The subject of digital image analysis deals with extracting relevant information from image data, stored in digital form in a computer. A fundamental problem in image analysis is image segmentation, i.e., the identification and separation of relevant objects and structures in an image. Accurate segmentation of objects of interest is often required before further processing and analysis can be performed.

Despite years of active research, fully automatic segmentation of arbitrary images remains an unsolved problem. Interactive, or semi-automatic, segmentation methods use human expert knowledge as additional input, thereby making the segmentation problem more tractable. The goal of interactive segmentation methods is to minimize the required user interaction time, while maintaining tight user control to guarantee the correctness of the results. Methods for interactive segmentation typically operate under one of two paradigms for user guidance: (1) Specification of pieces of the boundary of the desired object(s). (2) Specification of correct segmentation labels for a small subset of the image elements. These types of user input are referred to as boundary constraints and regional constraints, respectively.

This thesis concerns the development of methods for interactive segmentation, using a graph-theoretic approach. We view an image as an edge weighted graph, whose vertex set is the set of image elements, and whose edges are given by an adjacency relation among the image elements. Due to its discrete nature and mathematical simplicity, this graph based image representation lends itself well to the development of efficient, and provably correct, methods.

The contributions in this thesis may be summarized as follows:

  • Existing graph-based methods for interactive segmentation are modified to improve their performance on images with noisy or missing data, while maintaining a low computational cost.
  • Fuzzy techniques are utilized to obtain segmentations from which feature measurements can be made with increased precision.
  • A new paradigm for user guidance, that unifies and generalizes regional and boundary constraints, is proposed.

The practical utility of the proposed methods is illustrated with examples from the medical field.

sted, utgiver, år, opplag, sider
Uppsala: Acta Universitatis Upsaliensis, 2011. s. 61
Serie
Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Science and Technology, ISSN 1651-6214 ; 813
Emneord
Digital image analysis, Interactive image segmentation, Fuzzy image segmentation, Image foresting transform, Graph labeling, Graph cuts
HSV kategori
Forskningsprogram
Datoriserad bildbehandling
Identifikatorer
urn:nbn:se:uu:diva-149261 (URN)978-91-554-8037-0 (ISBN)
Disputas
2011-05-06, Häggsalen, Ångströmlaboratoriet, Lägerhyddsvägen 1, Uppsala, 10:15 (engelsk)
Opponent
Veileder
Tilgjengelig fra: 2011-04-14 Laget: 2011-03-16 Sist oppdatert: 2018-01-12bibliografisk kontrollert

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