A multilevel automatic thresholding method based on a genetic algorithm for a fast image segmentation
- Author
- HAMMOUCHE, Kamal1 ; DIAF, Moussa1 ; SIARRY, Patrick2
[1] Université Mouloud Mammeri, Département Automatique, Tizi-Ouzou, Algeria
[2] Laboratoire Images, Signaux et Systèmes Intelligents (LiSSi, EA 3956), Université Paris XII Val de Marne, 61 avenue du Général de Gaulle, 94010 Créteil, France - Source
Computer vision and image understanding (Print). 2008, Vol 109, Num 2, pp 163-175, 13 p ; ref : 30 ref
- CODEN
- CVIUF4
- ISSN
- 1077-3142
- Scientific domain
- Computer science
- Publisher
- Elsevier, San Diego, CA
- Publication country
- United States
- Document type
- Article
- Language
- English
- Author keyword
- Genetic algorithm Image segmentation Thresholding
- Keyword (fr)
- Algorithme génétique Algorithme rapide Détection seuil Histogramme Méthode raffinement Segmentation image Traitement image Transformation ondelette Vision ordinateur
- Keyword (en)
- Genetic algorithm Fast algorithm Threshold detection Histogram Refinement method Image segmentation Image processing Wavelet transformation Computer vision
- Keyword (es)
- Algoritmo genético Algoritmo rápido Detección umbral Histograma Método afinamiento Procesamiento imagen Transformación ondita Visión ordenador
- Classification
- Pascal
- 001 Exact sciences and technology / 001D Applied sciences / 001D02 Computer science; control theory; systems / 001D02C Artificial intelligence / 001D02C03 Pattern recognition. Digital image processing. Computational geometry
- Discipline
- Computer science : theoretical automation and systems
- Origin
- Inist-CNRS
- Database
- PASCAL
- INIST identifier
- 20028793
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
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DOI
10.1016/j.cviu.2007.09.001 
https://dx.doi.org/10.1016/j.cviu.2007.09.001
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