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DUGi: Ítem | Recercat - An information theoretic framework for image segmentation

Ítem


An information theoretic framework for image segmentation

In this paper, an information theoretic framework for image segmentation is presented. This approach is based on the information channel that goes from the image intensity histogram to the regions of the partitioned image. It allows us to define a new family of segmentation methods which maximize the mutual information of the channel. Firstly, a greedy top-down algorithm which partitions an image into homogeneous regions is introduced. Secondly, a histogram quantization algorithm which clusters color bins in a greedy bottom-up way is defined. Finally, the resulting regions in the partitioning algorithm can optionally be merged using the quantized histogram

IEEE

Autor: Rigau Vilalta, Jaume
Feixas Feixas, Miquel
Sbert, Mateu
Resum: In this paper, an information theoretic framework for image segmentation is presented. This approach is based on the information channel that goes from the image intensity histogram to the regions of the partitioned image. It allows us to define a new family of segmentation methods which maximize the mutual information of the channel. Firstly, a greedy top-down algorithm which partitions an image into homogeneous regions is introduced. Secondly, a histogram quantization algorithm which clusters color bins in a greedy bottom-up way is defined. Finally, the resulting regions in the partitioning algorithm can optionally be merged using the quantized histogram
Accés al document: http://hdl.handle.net/2072/94970
Llenguatge: eng
Editor: IEEE
Drets: Tots els drets reservats
Matèria: Algorismes computacionals
Imatges -- Segmentació
Imatges -- Processament
Imaging segmentation
Computer algorithms
Image processing
Títol: An information theoretic framework for image segmentation
Tipus: info:eu-repo/semantics/article
Repositori: Recercat

Matèries


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Autors


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