teorÍa de decisiÓn bayesiana en los criterios de similitud utilizados en la segmentaciÓn de imÁgenes de rango bayesian decision theory in similarity criteria used in range images segmentation
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ID: 209870
2007
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Abstract
El obtener una imagen segmentada correctamente sigue siendo un asunto sin resolverse. Por lo general los resultados obtenidos por un computador al segmentar una imagen contienen sobre-segmentaciones, sub-segmentaciones y bordes mal definidos. En gran parte, estos inconvenientes recaen sobre el criterio de similitud utilizado por los algoritmos de segmentación. En el presente artículo se hace un análisis de los criterios de similitud más utilizados en la literatura y de la utilización de criterios basados en la teoría de decisión bayesiana.
To obtain a segment image is still not possible. Typically, results obtained by computer programs show over-segmentation and not well-defined edges. Most of these difficulties are believed to be due to similarity criteria used by segmentation algorithms. In this paper, there is an analysis of similarity criteria most used in literature and an analysis of criteria based on Bayesian decision theory.
To obtain a segment image is still not possible. Typically, results obtained by computer programs show over-segmentation and not well-defined edges. Most of these difficulties are believed to be due to similarity criteria used by segmentation algorithms. In this paper, there is an analysis of similarity criteria most used in literature and an analysis of criteria based on Bayesian decision theory.
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daz2007revistateora
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| Authors | ;Idanis Díaz;Diana Montoya;Pierre Boulanger |
| Journal | plant cell and environment |
| Year | 2007 |
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