Image Thinning

1
Image Thinning

• Aria Rajasa Masna 1201000164
• Charles Gunawan 1201000237
• Rama Pandugita 1201000865
• Suluh Legowo 1201001039

2
Introduction

• What is thinning?
• Thinning is a morphological operation that is
  used to remove selected foreground pixels from
  binary image. The result of thinning operation is
  a single pixel thickness of the binary image.

3
How it works?

• Thinning operation is carried out by translating
  the origin of the structuring element (known as
  kernel) to each possible pixel position in the
  image, and at each such position comparing it
  with the underlying image pixels.
• If the foreground and background pixels in the
  structuring element exactly match the foreground
  and background pixels in the image, then the
  image pixel underneath the origin of the
  structuring elements is set to background.
  Otherwise it left unchanged.
• The choice of the structuring element determines
  under what situations a foreground pixel will be
  set to background, and hence it determines the
  application for thinning operation.
• The thinning operator is normally applied
  repeatedly until it causes no further changes to
  the image, although in some application may only
  be applied for limited number of iteration.

4
Thinning Algorithm

• Simple algorithm for thinning
• Consider all pixels on the boundaries of
  foreground regions (foreground points that have
  at least on background neighbor).
• Delete any such point that has more than one
  foreground neighbor, as long as doing so does not
  split the existing region.
• Iterate until no further change can be made
  (convergence).

5
Thinning Example

• Consider this simple binary image

6
Thinning Example (contd)

• Following structuring elements and all their 900
  rotations are structuring elements for
  skeletonization by morphological thinning.

Fig1.a
Fig1.b
7
Thinning Example (contd)

• At each iteration, the image is first thinned by
  kernel in fig1.a, and then by the kernel in
  fig1.b, and then with their remaining six 900
  rotations of the two kernels. The process
  repeated for each pixel in cyclic fashion until
  none of the thinning produces any further
  changes. The picture on the left show the
  iteration sequences for pixel at (0,0).

8
Thinning Result

• The following figure shows the result of the
  thinning operation.

9
Before And After Thinning (1)
10
Before And After Thinning (2)
Original Image
Binary Image
Thinned Image