Pattern recognition for sheet metal part models

• US 20060089738A1
• Filed: 10/25/2004
• Published: 04/27/2006
• Est. Priority Date: 10/25/2004
• Status: Active Grant

• Current Assignee: Amada Company Limited
• Original Assignee: Amada Company Limited
• Inventors: Sakai, Satoshi, Ishii, Masanobu
• Granted Patent: US 7,158,853 B2
• Time in Patent Office: Days
• US Class Current: 700/97
• CPC Class Codes: G06V 10/424 Syntactic representation, e.g. by using alphabets or grammars
• CPC Class Codes: G06V 10/435 Computation of moments

Abstract

Analysis is performed on sheet metal products to determine characteristics (or feature vectors) of the sheet metal products. Multiple feature vectors can be obtained for each sheet metal product. Exemplary analyses include a first order moment and a second order moment. The characteristics can be compared with characteristics of other sheet metal part shapes to determine how similar the shapes are.

Claims

1. A method of specifying characteristics of a sheet metal product, comprising:

obtaining feature vectors derived from at least one characteristic extraction method.

2. The method of claim 1, wherein the obtaining further comprises obtaining a feature vector derived by applying a moment as the characteristic extraction method of the sheet metal product.

3. The method of claim 1, further comprising:

comparing a feature vector of the sheet metal part product with a feature vector of another sheet metal part product; and

determining a level of similarity between the sheet metal part products based upon the comparison.

4. The method of claim 2, further comprising:

comparing a feature vector of the sheet metal part product with a feature vector of another sheet metal part product; and

determining a level of similarity between the sheet metal part products based upon the comparison.

5. The method of claim 2, in which the moment comprises a second order moment.

6. The method of claim 2, in which the moment comprises a first order moment.

7. The method of claim 2, in which the applying further comprises applying the moment to a 3D sheet metal part shape.

8. The method of claim 2, in which the applying further comprises applying the moment to a 2D sheet metal part shape.

9. The method of claim 2, in which the applying further comprises applying the moment to a 3D sheet metal part shape and applying the moment to a 2D sheet metal part shape.

10. The method of claim 1, further comprising obtaining at least one other feature vector of the sheet metal product,

and comparing feature vectors to determine a refined level of similarity, the comparing comprising comparing the plurality of feature vectors of the sheet metal product with a plurality of corresponding feature vectors of another sheet metal product to determine the refined degree of similarity between the sheet metal products.

11. The method of claim 10, in which a user selects the plurality of the feature vectors, and assigns a weight to each selected feature vector, the refined degree of similarity being determined based upon the assigned weights and the selected feature vectors.

12. The method of claim 1, wherein the obtaining further comprises obtaining a feature vector derived by performing a sheet metal CT scan cross section as the characteristic extraction method of the sheet metal product.

13. The method of claim 12, wherein the obtaining further comprises obtaining a feature vector derived by performing a UZ analysis as the characteristic extraction method of the sheet metal product.

14. A computer readable medium storing a program for specifying characteristics of a sheet metal product, comprising:

a feature vector code segment that obtains feature vectors derived from at least one characteristic extraction method.

15. The medium of claim 14, the feature vector code segment further comprising, obtaining a feature vector derived by applying a moment as the characteristic extraction method of the sheet metal product.

16. The medium of claim 14, further comprising:

a comparing code segment that compares a feature vector of the sheet metal part product with a feature vector of another sheet metal part product; and

a similarity code segment that determines a level of similarity between the sheet metal part products based upon the comparison.

17. The medium of claim 15, further comprising:

a comparing code segment that compares a feature vector of the sheet metal part product with a feature vector of another sheet metal part product; and

a similarity code segment that determines a level of similarity between the sheet metal part products based upon the comparison.

18. The medium of claim 15, in which the moment comprises a second order moment.

19. The medium of claim 15, in which the moment comprises a first order moment.

20. The medium of claim 14, in which the obtaining code segment further comprises obtaining at least one other feature vector of the sheet metal part shape,

and the medium further comprising a comparing code segment that compares feature vectors to determine a refined level of similarity, the comparing comprising comparing the plurality of feature vectors of the sheet metal product with a plurality of corresponding feature vectors of another sheet metal product to determine the refined degree of similarity between the sheet metal products.

21. The method of claim 20, further comprising an input receiving code segment that receives a user'"'"'s selection of the plurality of the feature vectors, and assignment of a weight to each selected feature vector, the refined degree of similarity being determined based upon the assigned weights and the selected feature vectors.

22. The medium of claim 14, wherein the obtaining code segment further comprises obtaining a feature vector derived by performing a sheet metal CT scan cross section as the characteristic extraction method of the sheet metal product.

23. The medium of claim 22, wherein the obtaining code segment further comprises obtaining a feature vector derived by performing a UZ analysis as the characteristic extraction method of the sheet metal product.

24. A method for searching for similar sheet metal part shapes, comprising:

inputting a freehand sketch representing a sheet metal part shape;

determining at least one feature vector of the input sheet metal part shape; and

comparing the at least one feature vector of the input sheet metal part shape with at least one corresponding feature vector of another sheet metal part shape to determine a degree of similarity between the sheet metal part shapes.

25. The method of claim 24, in which the inputting further comprises inputting a flat pattern outline.

26. The method of claim 24, in which the inputting further comprises inputting cross section lines.

27. The method of claim 24, in which the determining further comprises determining a plurality of feature vectors of the input sheet metal part shape, and

the comparing further comprises comparing the plurality of feature vectors of the input sheet metal part shape with a plurality of corresponding feature vectors of the other sheet metal part shape to determine a refined degree of similarity between the sheet metal part shapes.

28. A computer readable medium storing a program for searching for similar sheet metal part shapes, comprising:

an input code segment that accepts input of a freehand sketch representing a sheet metal part shape that is used as a key part shape;

a feature vector code segment that determines at least one feature vector of the key part shape; and

a similarity analysis code segment that compares the at least one feature vector of the key part shape with at least one corresponding feature vector of another sheet metal part shape to determine a degree of similarity between the sheet metal part shapes.

29. The medium of claim 28, in which the input code segment further accepts input of a flat pattern outline.

30. The medium of claim 28, in which the input code segment further accepts input of cross section lines.

31. The medium of claim 28, in which the feature vector code segment further determines a plurality of feature vectors of the key part shape, and

the similarity analysis code segment further compares the plurality of feature vectors of the key part shape with a plurality of corresponding feature vectors of the other sheet metal part shape to determine a refined degree of similarity between the sheet metal part shapes.