Morph Segmentation

Question 1

How do you define Morph Segmentation?

Answer 1

• operates on images as a set of points
• modify in a control way the morphology of an image
• used in binary images
• used in image processing for filtering, segmentation, object description
  It has basic and composed operations

Question 2

How many basic operations are there?

Answer 2

2

Question 3

What are the basic operations that morph segmentation allows?

Answer 3

• dilation
• erosion

Question 4

How do you define dilation?

Answer 4

• enlarges the boundaries
• small holes and gaps are filled

Question 5

How do define erosion?

Answer 5

• erode away the boundaries of regions of foreground
• holes and gaps are increased

Question 6

How many composed operations are there?

Answer 6

2

Question 7

What are the composed operations that morph segmentation allows?

Answer 7

• opening
• closing

Question 8

What characterizes opening?

Answer 8

• erosion followed by dilation
• union of all objects that fit in structuring element

Question 9

What characterizes closing?

Answer 9

• dilation followed by erosion
• dual to opening

Question 10

Can edge detection be done with morphology? If yes how does it work?

Answer 10

Yes
- erosion of objects then subtraction from original

Question 11

How is segmentation done?

Answer 11

• dividing image in regions
• applied before image analysis
• group pixels with similar properties
• no perfect segmentation method

Question 12

What is edge detection segmentation based in?

Answer 12

• pixel intensity
• regions
• edges

Question 13

What is thresholding?

Answer 13

• oldest segmentation method
• appropriate when object of interest have homogenous intensity different from background
• not easy to find the adequate value
• if value is uknown, analyze the histogram to choose an adequate value
  -For a bimodal histogram, the threshold value corresponds to the valley between the peaks

Question 14

Can this approach can produce classification errors depending on the image histogram and intensity of values of the objects?

Answer 14

Yes

Question 15

How many and what kind of approaches are there (thresholding)?

Answer 15

-There are 2 approaches:
- global
- variable

Question 16

How many variable approaches are there?

Answer 16

3
-Local
-Adaptive
- Otsu’s method

Question 17

Give me a example of thresholding

Answer 17

OCR -Optical Character Recognition:
Page ->Scanner -> OCR -> ASCII text

Question 18

Can the thresholding be applied to image
sub-regions?

Answer 18

Yes

Question 19

What defines the local variable approach?

Answer 19

It depends on properties of neighbouring pixels

Question 20

What defines the Adaptive variable approach?

Answer 20

It depends on spatial coordinates

Question 21

What defines the Otsu’s method variable approach?

Answer 21

It is based on probabilistic analysis obtained
from histogram

Question 22

What is region growing:

Answer 22

• grow a region by aggregation of pixels starting at a seed point
• all neighbouring pixels that comply the rule are labelled as belonging to the region

Question 23

Is obtaining a “good” seed pixels a problem ?

Answer 23

Yes

Question 24

How can seed be obtained?

Answer 24

Seed can be obtained using:
– Histograms
– Interactively
…

Question 25

How can flood filing be done?

Answer 25

It can be done using:
-recursive version;
-depth-first search;
-breadth-first search;