image segmentation & template matching

Image Segmentation&

Template Matching

Multimedia Signal Processing

lecture on 6.3.2007

Petri Hirvonen

Image Segmentation

Terminology

Image processing tools

Examples

Details of the Assignment

Tracking Rolling Leukocytes With Shape and Size Constrained Active Contours

Image segmentation based on maximum-likelihoodestimation and optimum entropy-distribution (MLE–OED)

Image segmentation problem is basically one of psychophysical perception, and therefore

not susceptible to a purely analytical solution.

Motivation: Image content representationRequirements: object definition & extraction

Mathematical morphology is very useful

for analyzing shapes in images.

Basic tools: dilation A+B and erosion A–B

Application: boundary detection

Internal boundary: A - (A–B)External boundary: (A+B) - A

Morphological gradient: (A+B) - (A–B)Assignment: object edges

A - (A–B) (A+B) - A (A+B) - (A–B)

Dilation:

Replace every point (x,y) in A with a copy of B centered at B(0,0)

The result D is the union of all translations.

Erosion:

The resulting set of points E consists ofall points for which B is in A.

0 0 0 0 0 0 1 1 0 0 0 1 1 0 0 0 1 1 0 0 0 1 1 1 0 0 0 1 1 0 0 0 0 0 0

1 0 1 0 1 0 1 0 1

0 1 0 1 1 1 0 1 0

A AD DE E

B B

Structuring element, kernel = B

Minkowski addition / subtraction

Image information

Segmenting SEM-images

max

min

)(&minargi

ikr

kbest pIpIkIDk

• Dilation of the thresholded block contains the thresholded gradient completely at the optimal threshold.

n

I

m

IGGI nm ,,

22nm GGM

(k and p are thresholds, D is dilationwith a structuring element of radius r)

max

min

)(&minargi

ikr

kbest pIpIkIDk

Information & colour

222

211_

2 groupwithin

2222

11_2

imageimagegroupbetween

• Nobuyuki Otsu, A Threshold Selection Method from Gray-Level Histograms, 1979

• For bimodal distributions

minimized

maximized

Histogram-based thresholdingOtsu’s method

kk

kkimagegroupbetween

1

2

_2

Probability of intensity k

Mean of group @ k

Hough transform Region Of Interest Histogram

)( 00 xxkyy 221

221 )()( yyxxd

Length and width are the perpendicular

distances on the original

(thresholded) target area.

Perimeter is computed by

the Chain Code algorithm.

Template Matching

f

h

),(),(),(),( * vuHvuFyxhyxf

)( *1 HFFc

We have first created a DATABASEthat contains the elements in the table.

FOR-loop is executed for all templatesFont_images{index}And the result is visualized in colours:

Scale ?Rotation ?

Object perimeter

Object perimeter