IMAGE ANALYSIS METHOD, IMAGE ANALYSIS SYSTEM AND USES THEREOF

• US 20100310129A1
• Filed: 12/05/2008
• Published: 12/09/2010
• Est. Priority Date: 12/05/2007
• Status: Abandoned Application

• Current Assignee: Max-Planck-Gesellschaft Zur Foerderung Der Wissenschaften e.V. (Max-Planck-Gesellschaft zur Frderung der Wissenschaften e)
• Original Assignee: Max-Planck-Gesellschaft Zur Foerderung Der Wissenschaften e.V. (Max-Planck-Gesellschaft zur Frderung der Wissenschaften e)
• Inventors: Höpfner, Sebastian
• Application Number:
  US12/746,283
• Publication Number:
  US 20100310129A1
• Time in Patent Office: Days
• US Class Current: 382/104
• CPC Class Codes: G06T 11/203 Drawing of straight lines or curves
• CPC Class Codes: G06T 2207/20044 Skeletonization; Medial axis transform
• CPC Class Codes: G06T 7/13 Edge detection
• CPC Class Codes: G06T 7/60 Analysis of geometric attributes
• CPC Class Codes: G06T 9/001 Model-based coding, e.g. wire frame
• CPC Class Codes: G06T 9/20 Contour coding, e.g. using detection of edges
• CPC Class Codes: G06V 30/10 Character recognition
• CPC Class Codes: G06V 30/168 Smoothing or thinning of the pattern; Skeletonisation
• CPC Class Codes: G06V 30/1823 using vector-coding
• CPC Class Codes: H04N 19/20 using video object coding
• CPC Class Codes: H04N 19/94 Vector quantisation

Abstract

The present invention relates to an image analysis method for analyzing a digital image comprising transforming object-pixels into a vector dataset. The vector for each object pixel comprises a positional, a directional and a distance component. The number of vectors in the dataset is reduced based on neighborhood criteria. The remaining vectors can code the object by means of a centerline and pointers to its contour.

Claims

1. Image analysis method for analyzing a digital image comprising a plurality of object-pixels that define at least one object in said digital image, wherein the image analysis method comprises the step of transforming at least one object-pixel into at least one vector in a vector dataset and wherein the at least one vector comprises a positional component, a directional component and a distance component.

2. Image analysis method according to claim 1, wherein the positional component of each vector is selected such that it defines the location of the respective transformed object-pixel and the distance and directional component of each vector is selected such that the transformed vector is a surface normal vector.

3. Image analysis method according to claim 1 or 2, wherein the transforming step of the method comprises the step:

(a) selecting the positional, directional and distance component of each vector such that the vector points from the respective object-pixel to the non-object pixel or to the group of non-object pixels that is located closest to said respective object-pixel;

4. The image analysis method according to any of claims 1 to 3, wherein the transforming step of the method comprises the step:

(b) adjusting the directional components of the vectors of the vector dataset such that the vectors are surface-normal vectors.

5. The image analysis method according to any of claims 1 to 4, wherein the method further comprises the step:

(c) selecting a subset of vectors in the vector dataset based on the directional component of the vectors in the vector dataset.

6. The image analysis method according to any of claims 3 to 5, wherein in step (a) each vector is determined by carrying out at least the following steps:

(i) selecting an object pixel (SOP);

(ii) selecting a circle (CC) which

(a1) is centered at the selected object pixel (SOP); and

(b1) contacts at least one object pixel; and

(c1) contacts at least one non-object pixel or a group of non-object pixels;

(iii) selecting a pixel (P) that contacts the circle (CC) and that defines the vector which points from the selected object pixel (SOP) to the selected pixel (P); and

(iv) optionally storing and/or transmitting the vector determined in step (iii).

7. The image analysis method according to any of claims 6, wherein the group of non-object pixels comprises at least two non-object pixels and wherein within said group of non-object pixels, each non-object pixel contacts at least one other non-object pixel of said group of non-object pixels.

8. The image analysis method according to any of claim 6 or 7, wherein the pixel (P) is selected from said group of non-object pixels.

9. The image analysis method according to any of claims 6 to 8, wherein in step (ii) the circle which has the smallest radius of all circles that fulfil criteria (ii)(a1), (ii)(b1) and (ii)(c1) is selected as the circle (CC).

10. The image analysis method according to any of claims 6 to 9, wherein in step (ii) the circle (CC) is selected from a group of circles each of which has a radius which does not differ by more than 10 pixels from the distance component of a vector of a previously transformed object-pixel which either contacts the selected object pixel (SOP) or which is localized not farther than 10 pixels away from the selected object pixel (SOP).

11. The image analysis method according to any of claims 4 to 10, wherein the adjusting step (b) comprises the step of:

selecting in step (iii) of step (a) a pixel which contacts the circle (CC) and which is located equidistant to two pixels each of which is localized at an intersection between a second circle (SCC) which

(a2) is centered at the selected object pixel (SOP); and

(b2) contacts at least one object pixel; and

(c2) contacts at least one non-object pixel; and

(d2) has a radius which is larger than the radius of the circle (CC); and

(e2) which contacts not more non-object pixels than object pixels; and

the boundary of the object in said digital image that comprises the selected object pixel (SOP),

as the pixel (P).

12. The image analysis method according to claim 11, wherein the intersection between the boundary of the object and the second circle (SCC) is the location of a group of pixels, wherein:

(a3) the group of pixels comprises at least one non-object pixel and at least two object-pixels; and

(b3) all pixels of said group of pixels contact the second circle (SCC); and

(c3) each object-pixel in said group of pixels contacts at least one other object-pixel in said group of pixels.

13. The image analysis method according to claim 5-12, wherein in the selection step (c) vectors are selected if they contact each other and if they have unequal directional components.

14. The image analysis method according to claim 5-13, wherein the selection step (c) comprises selecting vectors if they contact each other and if their directional components are sufficiently dissimilar such that at least 90% of said vectors comprise a positional component that defines a pixel on the medial axis of said object.

15. The image analysis method of any of claims 5-14, wherein the selection in step (c) is carried out by removing from said vector dataset any vector that does not have at least two neighbouring vectors, each of which forms with the vector an angle which is larger than about one eighth of the maximum angle which defines one complete circle.

16. The image analysis method of any of claims 5-15, wherein the selection step (c) comprises a step of removing from said vector dataset a vector if the vector does not fulfil the following two conditions:

(1) the vector has at least three neighbouring vectors each of which forms with the vector an angle which is larger than about one eighth of the maximum angle which defines one complete circle; and

(2) the vector has at least three neighbouring vectors each of which forms with the vector an angle which is smaller or equal than about one eighth of the maximum angle which defines one complete circle.

17. The image analysis method according to any of claims 6-16, wherein step (iii) and/or step (c) comprises the step of storing

(1) the location of the selected object pixel (SOP) in the digital image as the positional component of the at least one vector;

(2) the direction in which the pixel (P) is localized with respect to the selected object pixel (SOP) as the directional component of the at least one vector; and

/or

(3) the radius of the circle (CC) as the distance component of the at least one vector.

18. A computer program product stored on a computer readable storage medium comprising a computer-readable program code for causing a data processing system to carry out the image analysis method according to any of claims 1 to 17.

19. Apparatus for carrying out the image analysis method according to any of claims 1 to 17.

20. The apparatus of claim 19, wherein the apparatus comprises an electronic integrated circuit capable of carrying out the image analysis method according to any of claims 1 to 17;

wherein said method is not implemented as a program but as an electronic integrated circuit.

21. The apparatus of claim 19, wherein the electronic integrated circuit is an application-specific integrated circuit (ASIC).

22. Data processing system comprising a memory device, an operating system and the computer program product according to claim 18 which is loaded into the memory device of said data processing system and wherein the data processing system is capable of carrying out the image analysis method according to any of claims 1 to 17.

23. Image analysis system comprising an imaging device and the data processing system of claim 22 or the apparatus according to any of claims 19 to 21;

wherein the imaging device is capable of acquiring digital images and wherein the acquired digital images are transferred to said data processing system or said apparatus.

24. The image analysis system of claim 23, wherein the imaging device is selected from the group consisting of a digital camera, a computed tomography (CT) scanner, a magnetic resonance imaging (MRI) scanner, a positron emission tomography (PET) scanner, an ultrasonograph, an echo sonar, a night vision device, a flat-bed scanner, a database comprising one or more images, a fingerprinting device, a fax machine, a radar equipment and an X-ray imaging device.

25. The image analysis system according to claim 24, wherein the digital camera is mounted on a microscope or an endoscope.

26. The image analysis system according to claim 25, wherein the microscope is a light microscope or an electron microscope or an atomic force microscope.

27. System for controlling a vehicle travelling on a road, comprising:

(a4) a vehicle; and

(b4) an image analysis system according to claim 24, wherein the imaging device is a digital camera, a night vision device and/or a radar equipment; and

(c4) optionally a computational device which receives at least one vector dataset from the image analysis system and determines the relative position and the relative velocity of detected objects with respect to the position and velocity of the controlled vehicle; and

(d4) optionally a controlling device which receives the computed data from the computational device and controls the direction in which the vehicle is driving and the vehicle'"'"'s velocity such as to prevent the vehicle form leaving the sides of the road and/or to prevent a collision with an object on the road.

28. Use of the image analysis method according to any of claims 1 to 17, the data processing system of claim 22, the apparatus according to any of claims 19 to 21, or the image analysis system according to any of claims 23 to 26 in an application selected from the group consisting of medical image analysis, traffic control, vehicle guidance, automated product quality control, semiconductor chip topography quality control, semiconductor chip connector quality control, microscopy image analysis, similarity searches for similar digital images in a database, digital image compression and text recognition.