Preparing an Image

To receive good results with object detection methods in images, those images usually need some kind of preprocessing. Segmensation currently only offers such functions for images where objects are defined by their brightness.

Closing

Closing is an operator from the field of mathematical morphology that is usually used on binary or grayscale images. As the name implies, closing is an operator that removes small holes in objects. It also reduces general noise in images.

The operator consists of two steps: Dilation and Erosion. Dilation expands the area that is assigned to an object, while erosion shrinks it. Due to the way these two operations work, the borders of objects stay similar, but holes that are filled by dilation can not be opened again by erosion.

Note

For details on how closing works and corresponding examples, see this page from HIPR.

Parameters

Number of iterations for Dilation and Erosion.

image of GUI

Shrinking

Shrinking can be used to manipulate the color histogram of an image. With this operation, certain colors can be enhanced by reducing the color space to the desired range.

Note

This operation also automatically maps the color values to a range between 0 and 255, which is required for saving the image as JPG or PNG.

image of GUI
[HIPR]

Hypermedia Image Processing Reference - R. Fisher, S. Perkins, A. Walker and E. Wolfart