Computing device and method of determining border points for measuring images of objects

• US 8,885,946 B2
• Filed: 01/25/2013
• Issued: 11/11/2014
• Est. Priority Date: 02/29/2012
• Status: Expired due to Fees

• Current Assignee: Hong Fu Jin Precision Industry (Shenzhen) Co., Ltd. (Hon Hai Precision Industry Co., Ltd.), Hon Hai Precision Industry Co., Ltd.
• Original Assignee: Hong Fu Jin Precision Industry (Shenzhen) Co., Ltd. (Hon Hai Precision Industry Co., Ltd.), Hon Hai Precision Industry Co., Ltd.
• Inventors: Chang, Chih-Kuang, Jiang, Li, Yuan, Zhong-Kui, Zou, Zhi-Jun
• Primary Examiner(s): Liu, Li
• Application Number:
  US13/749,710
• Publication Number:
  US 20130223761A1
• Time in Patent Office: 655 Days
• Field of Search: None
• US Class Current: 382/199
• CPC Class Codes: G06T 7/13 Edge detection
• CPC Class Codes: G06T 7/181 involving edge growing; involving edge linking
• CPC Class Codes: G06T 7/60 Analysis of geometric attributes

Abstract

In a method of determining border points for measuring an image of an object using a computing device, grayscale values of pixel points in an image being measured are acquired, and definition values of the pixel points are computed according to the grayscale values. A line which intersects with the image being measured is constructed, and the definition values of the pixel point values in the lines are obtained. A location range of a border point of the image being measured is determined according to the definition values of the pixel point values in the line, and the border point is selected from the location range. A border line of the image being measured is fitted using the border points.

Claims

1. A computerized method of determining border points for measuring an image of an object, the method being executed by at least one processor of a computing device and comprising:

(a) acquiring grayscale values of pixel points in the image being measured by the at least one processor;

(b) computing definition values of the pixel points according to the grayscale values by the at least one processor;

(c) constructing a line which intersects with the image being measured, and obtaining the definition values of the pixel point values in the lines by the at least one processor;

(d) determining a location range of a border point of the image being measured using the definition values of the pixel point values in the line by the at least one processor;

(e) determining the border point from the location range by the at least one processor;

(f) repeating step (c) to (e) until all border points of the image being measured has been determined by the at least one processor; and

(g) fitting a border line of the image being measured using the border points, and outputting the border line by the at least one processor,

wherein step (e) comprises;

obtaining the grayscale values of the pixel points in the line to form a fourth array by the at least one processor;

computing a difference value of every two adjacent values in the fourth array to form a fifth array by the at least one processor;

computing a mean difference value of every two adjacent difference values in the fifth array to form a sixth array by the at least one processor; and

selecting a mean difference value from the sixth array, which is a maximum value in the location range, and determining that the pixel point corresponding to the selected mean difference value is the border point by the at least one processor.

2. The method according to claim 1, wherein the definition value of a pixel point P in the image being measured is computed by:

constructing a rectangle, which is centered at the pixel point P and contains n*n pixel points;

computing a difference value of the grayscale values of the pixel point P and each of the other (n−

1) pixel points; and

computing a sum of absolute values of the difference values to gain the definition value of the pixel point P.

3. The method according to claim 2, wherein n is an odd number except 1.

4. The method according to claim 1, wherein step (d) comprises:

obtaining the definition values of the pixel points in the line to form a first array by the at least one processor;

computing a mean definition value of every N sequential definition values in the first array to form a second array by the at least one processor;

computing a difference value of every two adjacent mean definition values in the second array to form a third array by the at least one processor; and

determining the location range according to a maximum difference value and a minimum difference value in the third array by the at least one processor.

5. The method according to claim 4, wherein N is an odd number except 1.

6. A computing device, comprising:

a storage device;

at least one processor; and

one or more modules that are stored in the storage device, and are executed by the at least one processor, the one or more modules comprising instructions to;

acquire grayscale values of pixel points in an image being measured of an object;

compute definition values of the pixel points according to the grayscale values;

construct a line which intersects with the image being measured, and obtain the definition values of the pixel point values in the lines;

determine a location range of a border point of the image being measured using the definition values of the pixel point values in the line;

determine the border point from the location range; and

fit a border line of the image being measured using the border points, and output the border line,

wherein the border point is determined by;

obtaining the grayscale values of the pixel points in the line to form a fourth array;

computing a difference value of every two adjacent values in the fourth array to form a fifth array;

computing a mean difference value of every two adjacent difference value values in the fifth array to form a sixth array; and

selecting a mean difference value from the sixth array, which is a maximum value in the location range, and determining that the pixel point corresponding to the selected difference mean value is the border point.

7. The computing device according to claim 6, wherein the definition value of a pixel point P in the image being measured is computed by:

constructing a rectangle, which is centered at the pixel point P and contains n*n pixel points;

computing a difference value of the grayscale values of the pixel point P and each of the other (n−

1) pixel points; and

computing a sum of absolute values of the difference values to gain the definition value of the pixel point P.

8. The computing device according to claim 7, wherein n is an odd number except 1.

9. The computing device according to claim 6, wherein the location range of is determined by:

obtaining the definition values of the pixel points in the line to form a first array;

computing a mean definition value of every N sequential definition values in the first array to form a second array;

computing a difference value of every two adjacent mean definition values in the second array to form a third array; and

determining the location range according to a maximum difference value and a minimum difference value in the third array.

10. The computing device according to claim 9, wherein N is an odd number except 1.

11. A non-transitory storage medium having stored thereon instructions that, when executed by a processor of a computing device, causes the processor to perform a method of determining border points for an image being measured of an object, wherein the method comprises:

(a) acquiring grayscale values of pixel points in the image being measured;

(b) computing definition values of the pixel points according to the grayscale values;

(c) constructing a line which intersects with the image being measured, and obtaining the definition values of the pixel point values in the lines;

(d) determining a location range of a border point of the image being measured using the definition values of the pixel point values in the line;

(e) determining the border point from the location range;

(f) repeating step (c) to (e) until all border points of the image being measured has been determined; and

(g) fitting a border line of the image being measured using the border points, and outputting the border line,

wherein step (e) comprises;

obtaining the grayscale values of the pixel points in the line to form a fourth array;

computing a difference value of every two adjacent values in the fourth array to form a fifth array;

computing a mean difference value of every two adjacent difference value values in the fifth array to form a sixth array; and

selecting a mean difference value from the sixth array, which is a maximum value in the location range, and determining that the pixel point corresponding to the selected mean difference value is the border point.

12. The non-transitory storage medium according to claim 11, wherein the definition value of a pixel point P in the image being measured is computed by:

constructing a rectangle, which is centered at the pixel point P and contains n*n pixel points;

computing a difference value of the grayscale values of the pixel point P and each of the other (n−

1) pixel points; and

computing a sum of absolute values of the difference values to gain the definition value of the pixel point P.

13. The non-transitory storage medium according to claim 12, wherein n is an odd number except 1.

14. The non-transitory storage medium according to claim 11, wherein step (d) comprises:

obtaining the definition values of the pixel points in the line to form a first array;

computing a mean definition value of every N sequential definition values in the first array to form a second array;

computing a difference value of every two adjacent mean definition values in the second array to form a third array; and

determining the location range according to a maximum difference value and a minimum difference value in the third array.

15. The non-transitory storage medium according to claim 14, wherein N is an odd number except 1.