Clustering stability for automated color image segmentation

Autor: Rafael Namías, Mónica G. Larese, Ariel E. Bayá
Rok vydání: 2017
Předmět:
Clustering high-dimensional data
Fuzzy clustering
Correlation clustering
ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION
02 engineering and technology
computer.software_genre
CLUSTERING VALIDATION
Artificial Intelligence
CURE data clustering algorithm
0202 electrical engineering
electronic engineering
information engineering
CLUSTERING STABILITY
Cluster analysis
Mathematics
IMAGE SEGMENTATION
business.industry
Segmentation-based object categorization
General Engineering
020207 software engineering
Pattern recognition
Spectral clustering
Ciencias de la Computación
Computer Science Applications
Ciencias de la Computación e Información
Canopy clustering algorithm
020201 artificial intelligence & image processing
Artificial intelligence
Data mining
business
computer
CIENCIAS NATURALES Y EXACTAS
Zdroj: Expert Systems with Applications. 86:258-273
ISSN: 0957-4174
DOI: 10.1016/j.eswa.2017.05.064
Popis: Clustering is a well-established technique for segmentation. However, clustering validation is rarely used for this purpose. In this work we adapt a clustering validation method, Clustering Stability (CS), to automatically segment images. CS is not limited by image dimensionality nor by the clustering algorithm. We show clustering and validation acting together as a data-driven process able to find the optimum number of partitions according to our proposed color-texture feature representation. We also describe how to adapt CS to detect the best settings required for feature extraction. The segmentation solutions found by our method are supported by a stability score named STI, which provides an objective quantifiable metric to obtain the final segmentation results. Furthermore, the STI allows to compare multiple alternative solutions and select the most appropriate according to the index meaning. We successfully test our procedure on texture and natural images, and 3D MRI data. Fil: Baya, Ariel Emilio. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas. Universidad Nacional de Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas; Argentina Fil: Larese, Monica Graciela. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas. Universidad Nacional de Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas; Argentina Fil: Namias, Rafael. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas. Universidad Nacional de Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas; Argentina
Databáze: OpenAIRE
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