Opening (morphology)

The opening of the dark-blue square by a disk, resulting in the light-blue square with round corners.

In mathematical morphology, opening is the dilation of the erosion of a set A by a structuring element B:

$A\circ B=(A\ominus B)\oplus B,\,$

where $\ominus$ and $\oplus$ denote erosion and dilation, respectively.

Together with closing, the opening serves in computer vision and image processing as a basic workhorse of morphological noise removal. Opening removes small objects from the foreground (usually taken as the bright pixels) of an image, placing them in the background, while closing removes small holes in the foreground, changing small islands of background into foreground. These techniques can also be used to find specific shapes in an image. Opening can be used to find things into which a specific structuring element can fit (edges, corners, ...).

One can think of B sweeping around the inside of the boundary of A, so that it does not extend beyond the boundary, and shaping the A boundary around the boundary of the element.

Properties

• Opening is idempotent, that is, $(A\circ B)\circ B=A\circ B$.
• Opening is increasing, that is, if $A\subseteq C$, then $A\circ B\subseteq C\circ B$.
• Opening is anti-extensive, i.e., $A\circ B\subseteq A$.
• Opening is translation invariant.
• Opening and closing satisfy the duality $A\bullet B=(A^{c}\circ B^{c})^{c}$, where $\bullet$ denotes closing.

Opening by reconstruction

In morphological opening $(A\ominus B)\oplus B$ , erosion operation removes objects that are smaller than structuring element B and dilation operation restores the shape of remaining objects. However, restoring accuracy in dilation operation highly depends on the type of structuring element and the shape of restoring objects. The opening by reconstruction method is able to restore the objects completely after erosion applied. It is defined as the reconstruction by geodesic dilation of $n$ erosions of $F$ by $B$ with respect to $F$ :

$O_{R}^{(n)}(F)=R_{F}^{D}[(F\ominus nB)],$

where $(F\ominus nB)$ denotes a marker image and $F$ is a mask image in morphological reconstruction by dilation. $R_{F}^{D}[(F\ominus nB)]=D_{F}^{(k)}[(F\ominus nB)],$ $D$ denotes geodesic dilation with $k$ iterator until stability such that $D_{F}^{(k)}[(F\ominus nB)]=D_{F}^{(k-1)}[(F\ominus nB)].$ Since $D_{F}^{(1)}[(F\ominus nB)]=([(F\ominus nB)]\oplus B)\cap F$ the marker image is limited the growth region by mask image, the dilation operation on marker image will not expand beyond mask image so that the marker image is subset of mask image $(F\ominus nB)\subseteq F.$

The images below present a simple opening-by-reconstruction example which extracts the vertical strokes from an input text image. Since the original image is converted from grayscale to binary image, it has few distortions in some characters so that same characters might have different vertical lengths. In this case, the structuring element is an 8-pixel vertical line which is applied in erosion operation in order to find objects of interest. Moreover, morphological reconstruction by dilation, $R_{F}^{D}[(F\ominus nB)]=D_{F}^{(k)}[(F\ominus nB)]$ iterates $k=9$ times until resulting image converge.

Original image for opening by reconstruction

Marker image

Result of opening by reconstruction

See also

• Mathematical morphology
• Closing
• Dilation
• Erosion

Bibliography

• Image Analysis and Mathematical Morphology by Jean Serra, ISBN 0-12-637240-3 (1982)
• Image Analysis and Mathematical Morphology, Volume 2: Theoretical Advances by Jean Serra, ISBN 0-12-637241-1 (1988)
• An Introduction to Morphological Image Processing by Edward R. Dougherty, ISBN 0-8194-0845-X (1992)

External links

• http://homepages.inf.ed.ac.uk/rbf/HIPR2/open.htm - Morphological Opening

References

• Digital Image Processing (Third Edition) by Rafael C. Gonzalez and Richard E. Woods, ISBN 978-93-325-7032-0(2008)