Grayscale Image Segmentation Based on Associative Memories
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Redalyc
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| Formato: | Artículo científico |
| Lenguaje: | en |
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Instituto Politécnico Nacional
2011
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| _version_ | 1876453263985868800 |
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| author | Enrique Guzmán Ramírez |
| author_facet | Enrique Guzmán Ramírez |
| contents | Grayscale Image Segmentation Based on Associative Memories Enrique Guzmán Ramírez Ofelia M. C. Jiménez Alejandro D. Pérez Oleksiy Pogrebnyak Computación Image segmentation associative memories clustering techniques In this paper, a grayscale image segmentation algorithm based on Extended Associative Memories (EAM) is proposed. The algorithm is divided into three phases. First, the uniform distribution of the image pixel values is determined by means of the histogram technique. The result of this phase is a set of regions (classes) where each one is grouped into a certain number of pixel values. Second, the EAM training phase is applied to the information obtained at the first phase. The result of the second phase is an associative network that contains the centroids group of each of the regions in which the image will be segmented. Finally, the centroid to which each pixel belongs is obtained using the EAM classification phase, and the image segmentation process is completed. A quantitative analysis and comparative performance for frequently-used image segmentation by the clustering method, the k-means, and the proposed algorithm when it uses prom and med operators are presented. 2011 artículo científico 1405-5546 https://www.redalyc.org/articulo.oa?id=61520938003 en http://www.redalyc.org/revista.oa?id=615 Computación y Sistemas application/pdf Instituto Politécnico Nacional Computación y Sistemas (México) Num.2 Vol.15 |
| format | Artículo científico |
| id | redalyc_61520938003 |
| institution | Redalyc |
| language | en |
| publishDate | 2011 |
| publisher | Instituto Politécnico Nacional |
| spellingShingle | Grayscale Image Segmentation Based on Associative Memories Enrique Guzmán Ramírez Computación Image segmentation associative memories clustering techniques Grayscale Image Segmentation Based on Associative Memories Enrique Guzmán Ramírez Ofelia M. C. Jiménez Alejandro D. Pérez Oleksiy Pogrebnyak Computación Image segmentation associative memories clustering techniques In this paper, a grayscale image segmentation algorithm based on Extended Associative Memories (EAM) is proposed. The algorithm is divided into three phases. First, the uniform distribution of the image pixel values is determined by means of the histogram technique. The result of this phase is a set of regions (classes) where each one is grouped into a certain number of pixel values. Second, the EAM training phase is applied to the information obtained at the first phase. The result of the second phase is an associative network that contains the centroids group of each of the regions in which the image will be segmented. Finally, the centroid to which each pixel belongs is obtained using the EAM classification phase, and the image segmentation process is completed. A quantitative analysis and comparative performance for frequently-used image segmentation by the clustering method, the k-means, and the proposed algorithm when it uses prom and med operators are presented. 2011 artículo científico 1405-5546 https://www.redalyc.org/articulo.oa?id=61520938003 en http://www.redalyc.org/revista.oa?id=615 Computación y Sistemas application/pdf Instituto Politécnico Nacional Computación y Sistemas (México) Num.2 Vol.15 |
| title | Grayscale Image Segmentation Based on Associative Memories |
| topic | Computación Image segmentation associative memories clustering techniques |
| url | https://www.redalyc.org/articulo.oa?id=61520938003 |