Model-based halftoning for color image segmentation

Publikation: Bidrag til tidsskrift › Konferenceartikel › Forskning › fagfællebedømt

Standard

Model-based halftoning for color image segmentation. / Puzicha, J; Belongie, S.

I: International Conference on Pattern Recognition, 2000, s. 629-632.

Publikation: Bidrag til tidsskrift › Konferenceartikel › Forskning › fagfællebedømt

Harvard

Puzicha, J & Belongie, S 2000, 'Model-based halftoning for color image segmentation', International Conference on Pattern Recognition, s. 629-632.

APA

Puzicha, J., & Belongie, S. (2000). Model-based halftoning for color image segmentation. International Conference on Pattern Recognition, 629-632.

Vancouver

Puzicha J, Belongie S. Model-based halftoning for color image segmentation. International Conference on Pattern Recognition. 2000;629-632.

Author

Puzicha, J ; Belongie, S. / Model-based halftoning for color image segmentation. I: International Conference on Pattern Recognition. 2000 ; s. 629-632.

Bibtex

@inproceedings{bd914dba6731420ab774d4639e66807b,
title = "Model-based halftoning for color image segmentation",
abstract = "Grouping algorithms based on histograms over measured image features have very successfully been applied to textured image segmentation [2, 11, 6]. However; the competing goals of statistical estimation significance demanding few quantization levels versus the necessary richness in representation often prevent a successful application for the color cue, since quantization may result in contouring.In this paper, we combine a novel halftoning technique called spatial quantization with distribution-based grouping algorithms to synthesize a powerful color image segmentation technique. The spatial quantization simultaneously determines color palette and halftoning by optimizing a joint cost function. It therefore allows for a highly adapted image representation with a smooth transition of color distributions for non-constant image surfaces.",
author = "J Puzicha and S Belongie",
year = "2000",
language = "English",
pages = "629--632",
journal = "Proceedings - International Conference on Pattern Recognition",
issn = "1051-4651",
publisher = "I E E E Computer Society",
note = "15th International Conference on Pattern Recognition (ICPR-2000) ; Conference date: 03-09-2000 Through 07-09-2000",

}

RIS

TY - GEN

T1 - Model-based halftoning for color image segmentation

AU - Puzicha, J

AU - Belongie, S

PY - 2000

Y1 - 2000

N2 - Grouping algorithms based on histograms over measured image features have very successfully been applied to textured image segmentation [2, 11, 6]. However; the competing goals of statistical estimation significance demanding few quantization levels versus the necessary richness in representation often prevent a successful application for the color cue, since quantization may result in contouring.In this paper, we combine a novel halftoning technique called spatial quantization with distribution-based grouping algorithms to synthesize a powerful color image segmentation technique. The spatial quantization simultaneously determines color palette and halftoning by optimizing a joint cost function. It therefore allows for a highly adapted image representation with a smooth transition of color distributions for non-constant image surfaces.

AB - Grouping algorithms based on histograms over measured image features have very successfully been applied to textured image segmentation [2, 11, 6]. However; the competing goals of statistical estimation significance demanding few quantization levels versus the necessary richness in representation often prevent a successful application for the color cue, since quantization may result in contouring.In this paper, we combine a novel halftoning technique called spatial quantization with distribution-based grouping algorithms to synthesize a powerful color image segmentation technique. The spatial quantization simultaneously determines color palette and halftoning by optimizing a joint cost function. It therefore allows for a highly adapted image representation with a smooth transition of color distributions for non-constant image surfaces.

M3 - Conference article

SP - 629

EP - 632

JO - Proceedings - International Conference on Pattern Recognition

JF - Proceedings - International Conference on Pattern Recognition

SN - 1051-4651

T2 - 15th International Conference on Pattern Recognition (ICPR-2000)

Y2 - 3 September 2000 through 7 September 2000

ER -

ID: 302162220