11.8. Simple Linear Iterative Clustering (SLIC)
| 11. Filtros artísticos |

### 11.8. Simple Linear Iterative Clustering (SLIC)

#### 11.8.1. Visión general

This filter creates superpixels based on k-means clustering.

Superpixels are small cluster of pixels that share similar properties. Superpixels simplifies images with a great number of pixels making them more easy to be treated in many domains (computer vision, pattern recognition and machine intelligence). GIMP's aim is more humble: create a posterization effect.

k-means clustering is one of the most used algorithms to create superpixels. Superpixel color is the mean of pixels color in the corresponding region.

#### 11.8.2. Activar el filtro

This filter is found in the image window menu under Filters → Artistic → Simple Linear Iterative Clustering….

#### 11.8.3. Opciones

Figura 17.198. “Simple Linear Iterative Clustering” options

Presets, Preview, Split view

  | Nota
  Estas opciones se describen en la Sección 2, “Características comunes”.

Tamaño de las regiones

  Increasing regions size collects more pixels, and so superpixels size increases also.

  Figura 17.199. Ejemplo de “Tamaño de las regiones”

  Tamaño de las regiones = 16

  Tamaño de las regiones = 32

Compactness

  Superpixels borders may be irregular. Increasing this option gives superpixels more regular border.

  Figura 17.200. “Compactness” example

  Compactness = 20

  Compactness = 40: look at the dome.

Iteraciones

  How many times filter is repeated. Increasing this value gives more details.

  Figura 17.201. Ejemplo de “Tamaño de las regiones”

  Iteraciones = 1 (predeterminado)

  Iteraciones = 15

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