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2014 | OriginalPaper | Buchkapitel

Image Segmentation Using Diffusion Tracking Algorithm with Patch Oversampling

verfasst von : Lassi Korhonen, Keijo Ruotsalainen

Erschienen in: E-Business and Telecommunications

Verlag: Springer Berlin Heidelberg

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Abstract

An image segmentation process can be considered as a process of solving a pixel clustering problem. This paper represents and combines a new clustering algorithm that we call as a Diffusion Tracking (DT) algorithm and a new clustering based image segmentation algorithm. The DT algorithm is related to classical spectral clustering techniques but overcomes some of their problems which guarantees a better starting point for the image segmentation process. The image segmentation process introduced in this paper joins seamlessly to the DT algorithm but can also be used together with other clustering methods like k-means. The segmentation algorithm is based on oversampling pixels from classified patches and using simple statistical methods for joining the information collected. The experimental results at the end of this paper show clearly that the algorithms proposed suit well also for very demanding segmentation tasks.

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Metadaten
Titel
Image Segmentation Using Diffusion Tracking Algorithm with Patch Oversampling
verfasst von
Lassi Korhonen
Keijo Ruotsalainen
Copyright-Jahr
2014
Verlag
Springer Berlin Heidelberg
DOI
https://doi.org/10.1007/978-3-662-44791-8_13

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