Image segmentation

• US 20040258305A1
• Filed: 08/13/2004
• Published: 12/23/2004
• Est. Priority Date: 06/27/2001
• Status: Abandoned Application

• Current Assignee: Coventry University
• Original Assignee: Coventry University
• Inventors: Haas, Olivier, Burnham, Keith J., Bueno, Maria Gloria
• Application Number:
  US10/482,196
• Publication Number:
  US 20040258305A1
• Time in Patent Office: Days
• US Class Current: 382/171
• CPC Class Codes: G06T 2207/10081 Computed x-ray tomography [CT]
• CPC Class Codes: G06T 2207/20152 Watershed segmentation
• CPC Class Codes: G06T 2207/20156 Automatic seed setting
• CPC Class Codes: G06T 2207/30008 Bone
• CPC Class Codes: G06T 7/0012 Biomedical image inspection
• CPC Class Codes: G06T 7/11 Region-based segmentation
• CPC Class Codes: G06T 7/136 involving thresholding
• CPC Class Codes: G06T 7/155 involving morphological operators
• CPC Class Codes: G06T 7/187 involving region growing; involving region merging; involving connected component labelling
• CPC Class Codes: G06V 10/267 by performing operations on regions, e.g. growing, shrinking or watersheds
• CPC Class Codes: G06V 2201/03 Recognition of patterns in medical or anatomical images

Abstract

In a method of segmenting an image a first seed pixel unit is selected from a first group of pixel units in which the pixel units all have substantially the same grey-level intensity. The grey-level intensity of said first pixel unit is compared with the grey-level intensity of each of selected adjacent pixel units of said image and those pixel units with grey levels within a selected range arm assigned as a pixel unit of the same region as said first pixel unit This comparison process is repeated for each of the pixel units in the image, those already having been assigned being ignored. A further seed pixel unit is selected from a further group of pixel units in which the pixel units all have substantially the same grey-level intensity and the comparison process repeated for all of the unassigned pixel units. Further seed pixel units are selected and the comparison process repeated until all the pixel units of the image have been assigned. A watershed transform is then applied to provide the segmented image.

Claims

1. A method of segmenting an image comprising:

(a) selecting a first pixel unit from a first group of pixel units in which the pixel units all have substantially the same grey-level intensity;

(b) selecting a first grey-level intensity range relative to the grey-level intensity of said first pixel unit;

(c) comparing the grey-level intensity of said first pixel unit with the grey-level intensity of each of selected adjacent pixel units of said image;

(d) assigning each said selected adjacent pixel unit as a pixel unit of the same region as said first pixel unit in response to the grey-level intensity of said adjacent pixel unit falling within said first grey-level intensity range;

(e) comparing the grey-level intensity of said first pixel unit with the grey-level intensity of each of selected next adjacent pixel units of said image;

(f) assigning each said selected next adjacent pixel unit as a pixel unit of the same region as said first pixel unit in response to the grey-level intensity of said next adjacent pixel unit falling within said first grey-level intensity range;

(g) repeating steps (e) and (f) for each of the pixel units in the image;

(h) selecting a further pixel unit from a further group of pixel units in which the pixel units have substantially the same grey-level intensity;

(i) selecting a further grey-level intensity range relative to the grey-level intensity of said further pixel unit;

(j) comparing the grey-level intensity of said further pixel unit with the grey-level intensity of each of selected adjacent pixel units of said image, wherein each selected adjacent pixel unit which is already assigned as a pixel unit of a region is ignored;

(k) assigning each unassigned said selected adjacent pixel unit as a pixel unit of the same region as said further pixel unit in response to the grey-level intensity of said selected adjacent pixel unit falling within said further grey-level intensity range;

(l) comparing the grey-level intensity of said further pixel unit with the grey-level intensity of each of selected next adjacent pixel units of said image;

(m) assigning each said unassigned selected next adjacent pixel unit as a pixel unit of the same region as said further pixel unit in response to the grey-level intensity of said selected next adjacent pixel unit falling within said further grey-level intensity range;

(n) repeating steps (l) and (m) for each of the pixel units in the image;

(O) and repeating steps (h) to (n) until all of the pixel units in the image have been assigned to a region.

2. A method as claimed in claim 1 wherein:

said first group of pixel units is the largest group of pixel units in the image;

and said further group of pixel units is the next largest group of pixel units.

3. A method as claimed in claim 1 further comprising the steps of:

(p) building a mosaic image;

(q) deriving the gradient of the mosaic image; and

(r) applying a watershed transform to said gradient to provide said segmented image.

4. A method as claimed in claim 3 further comprising the step of applying a merging operation to said segmented image to reduce segmentation of the image.

5. A method as claimed in claim 4 wherein a region is merged into an adjacent region if the number of pixel units in said region is less than a preselected number.

6. A method as claimed in claim 1 wherein each said pixel unit is a single pixel.

7. A method as claimed in claim 1 wherein the step of selecting said first and further pixel units comprises creating a frequency histogram of the grey level values of said image and selecting a predetermined grey level value in each distribution of said histogram to define said first and further pixel units.

8. A method as claimed in claim 7 wherein the predetermined grey level value for said first pixel unit is chosen from the largest distribution in the histogram, and for each successive further pixel unit is chosen from the next successive largest distribution in the histogram.

9. A method as claimed in claim 7 wherein said predetermined grey level is the average grey level of the distribution.

10. A method as claimed claim 1 wherein the distribution is a Gaussian distribution and each adjacent pixel unit is assigned to a region when the following condition is met:

|L_ave−

L_(x,y)|≦

T_w where;

L_ave=the average grey level intensity of the distribution;

L_(x,y)=the grey level intensity of the selected pixel unit in the distribution; and

T_w=a preselected threshold parameter value in the distribution.

11. A method as claimed in claim 10 wherein Lave is the peak value grey level and T_w=(L_max−

L_min)/2, where L_max and L_min are preselected upper and lower grey level values for the distribution.

12. A method as claimed in claim 1 wherein the distribution is a non Gaussian distribution and each adjacent pixel unit is assigned to a region when the following conditions are met:

L_(xy)−

L_ave≦

T_w1 for L_(xy)>

L_ave L_ave−

L_(xy)≦

T_w2 for L_(xy)<

L_ave where;

L_ave=a preselected grey level intensity within the distribution;

L_(x,y)=the grey level intensity of the selected pixel unit;

T_w1=a preselected lower threshold parameter value in the distribution; and

T_w2=an upper preselected threshold parameter value in the distribution.

13. A method as claimed in claim 12 wherein the value of L_ave is obtained from a statistical analysis of at least a portion of the distribution.

14. A method as claimed in claim 13 wherein value of L_ave is equal to the mean of a selected sample region within the distribution.

15. A method as claimed in claim 13 wherein said selected sample region comprises a 20×

20 pixel matrix.

16. A method of segmenting an image comprising:

selecting a pixel unit from a first group of pixel units in which the pixel units all have substantially the same grey-level intensity;

comparing the grey-level intensity of said first pixel unit with the grey-level intensity of each of a plurality of selected pixel units of said image;

assigning each said selected pixel unit as a pixel unit of the same region as said first pixel unit in response to the grey-level intensity of said adjacent pixel unit falling within a preselected grey-level intensity range;

selecting a further pixel unit from a further group of pixel units in which the pixel units have substantially the same grey-level intensity;

comparing the grey-level intensity of said further pixel unit with the grey-level intensity of each of a plurality of selected pixel units of said image, wherein each selected adjacent pixel unit which is already assigned as a pixel unit of a region is ignored;

assigning each unassigned said selected pixel unit as a pixel unit of the same region as said further pixel unit in response to the grey-level intensity of said selected adjacent pixel unit falling within a preselected further grey-level intensity range;

and repeating the above steps until all of the pixel units in the image have been assigned to a region.