Method and system for detecting the quality of debarking at the surface of a wooden log

1. A method for detecting the quality of debarking at the surface of a wooden log, comprising the steps of:

i) measuring a three-dimensional profile of at least a portion of the log surface to generate a corresponding profile image indicating the relative positions of points on said log surface in three-dimensional space;

ii) processing said profile image to detect edges therein by comparing said relative positions with one another and generate data indicative of the texture of said log surface, said texture data comprising the positions of said detected edges within said profile image; and

iii) analyzing said texture data to generate resulting data on parameters related to the debarking quality of said log surface, said parameters including fiber loss and residual bark.

2. The debarking quality detecting method of claim 1 , further comprising the step of:

iv) comparing log surface areas respectively characterized by said fiber loss and residual bark with said log surface to estimate fiber loss level and residual bark level.

3. The debarking quality detecting method of claim 2 , further comprising before step iv) the step of defining a plurality of surface sections of said log surface including a leading end section, a body section and a trailing end section, wherein said fiber loss level and residual bark level are estimated for one or more of said sections.

4. The debarking quality detecting method of claim 3 , wherein said fiber loss level and residual bark level are estimated for at least two of said sections using predetermined weighting factors assigned thereto on the basis of their relative importance in debarking quality detection.

5. The debarking quality detecting method of claim 1 , further comprising the step of:

iv) generating from the resulting data a two-dimensional image representing areas of said log surface respectively characterized by said detected fiber loss and detected residual bark.

6. The debarking quality detecting method of claim 5 , wherein said measurement of the three-dimensional profile is performed with respect to a pair of orthogonal reference axis characterized by different resolution levels, said image generating step iv) includes scaling the resulting data to compensate for the resolution difference.

7. The debarking quality detecting method of claim 1 , wherein said edges include vertical and horizontal edges of said profile image with respect to a substantially longitudinal axis of said wooden log to obtain said texture data.

8. The debarking quality detecting method of claim 7 , wherein said analyzing step iii) includes comparing said detected vertical and horizontal edges as part of said texture data to provide an indication of the ratio of said fiber loss with respect to said residual bark.

9. The debarking quality detecting method of claim 7 , wherein said processing step ii) further includes processing said detected vertical and horizontal edges to obtain said texture data as an indication of roughness of said log surface.

10. The debarking quality detecting method of claim 1 , wherein said processing step ii) includes flattening said profile image to compensate for the generally curved shape of said log surface.

11. The debarking quality detecting method of claim 10 , wherein said profile image flattening is performed by applying thereto a high-pass spatial frequency filter.

12. The debarking quality detecting method of claim 10 , wherein said profile image flattening is performed by applying thereto a curve-fitting algorithm.

13. The debarking quality detecting method of claim 9 , further comprising the step of:

iv) measuring light reflection from said log surface portion to generate corresponding reflected light intensity image data; and

v) comparing with a predetermined intensity threshold the reflected light intensity data to provide a further indication of the residual bark in addition to said resulting data.

14. The debarking quality detecting method of claim 13 , wherein said measuring step iv) includes correcting said light intensity image data to compensate for the generally curved shape of said log surface.

15. The debarking quality detecting method of claim 13 , further comprising the step of:

vi) generating from the resulting data a two-dimensional image representing areas of said log surface respectively characterized by said detected fiber loss, said detected residual bark, and a detected roughness value lower than a predetermined roughness threshold.

16. A system for detecting the quality of debarking at the surface of a wooden log, comprising:

a three-dimensional profile measuring unit for scanning at least a portion of the log surface to generate a corresponding profile image indicating the relative positions of points on said log surface in three-dimensional space;

data processing means for receiving and processing said profile image to detect edges therein by comparing said relative positions with one another and generate data indicative of the texture of said log surface, said texture data comprising the positions of said detected edges within said profile image; and

data analyzing means for receiving said texture data to generate resulting data on parameters related to the debarking quality of said log surface, said parameters including fiber loss and residual bark.

17. The debarking quality detecting system of claim 16 , wherein said data processing means is for detecting vertical and horizontal edges of said profile image with respect to a substantially longitudinal axis of said wooden log and for processing of said detected vertical and horizontal edges to obtain said texture data as an indication of roughness of said log surface, said system further comprising:

means for measuring light reflection from said log surface portion to generate corresponding reflected light intensity image data; and

further data analyzing means for comparing with a predetermined intensity threshold the reflected light intensity data to provide a further indication of the residual bark in addition to said resulting data.

18. A non-transitory software product data recording media in which program code is stored, said program code will cause a computer to perform a method for detecting the quality of debarking at the surface of a wooden log, from a three-dimensional profile image of at least of portion of a surface of said log, said profile image indicating the relative positions of points on said log surface in three-dimensional space, said method comprising the steps of:

i) processing said profile image to detect edges therein by comparing said relative positions with one another and generate data indicative of the texture of said log surface, said texture data comprising the positions of said detected edges within said profile image; and

ii) analyzing said texture data to generate resulting data on parameters related to the debarking quality of said log surface, said parameters including fiber loss and residual bark.

19. The non-transitory software product data recording media of claim 18 , wherein said method further comprising the step of:

iii) comparing log surface areas respectively characterized by said fiber loss and residual bark with said log surface to estimate fiber loss level and residual bark level.

20. The non-transitory software product data recording media of claim 19 , wherein said method further comprising before step iii) the step of defining a plurality of surface sections of said log surface including a leading end section, a body section and a trailing end section, wherein said fiber loss level and residual bark level are estimated for one or more of said sections.

21. The non-transitory software product data recording media of claim 20 , wherein said fiber loss level and residual bark level are estimated for at least two of said sections using predetermined weighting factors assigned thereto on the basis of their relative importance in debarking quality detection.

22. The non-transitory software product data recording media of claim 18 , wherein said method further comprising the step of:

iii) generating from the resulting data a two-dimensional image representing areas of said log surface respectively characterized by said detected fiber loss and detected residual bark.

23. The non-transitory software product data recording media of claim 22 , wherein said three-dimensional profile image is generated by measuring the three-dimensional profile of said log surface with respect to a pair of orthogonal reference axis characterized by different resolution levels, said image generating step iii) includes scaling the resulting data to compensate for the resolution difference.

24. The non-transitory software product data recording media of claim 18 , wherein said edges include vertical and horizontal edges of said profile image with respect to a substantially longitudinal axis of said wooden log to obtain said texture data.

25. The non-transitory software product data recording media of claim 24 , wherein said analyzing step ii) includes comparing said detected vertical and horizontal edges as part of said texture data to provide an indication of the ratio of said fiber loss with respect to said residual bark.

26. The non-transitory software product data recording media of claim 25 , wherein said processing step i) further includes processing said detected vertical and horizontal edges to obtain said texture data as an indication of roughness of said log surface.

27. The non-transitory software product data recording media of claim 18 , wherein said processing step i) includes flattening said profile image to compensate for the generally curved shape of said log surface.

28. The non-transitory software product data recording media of claim 27 , wherein said profile image flattening is performed by applying thereto a high-pass spatial frequency filter.

29. The non-transitory software product data recording media of claim, 27 wherein said profile image flattening is performed by applying thereto a curve-fitting algorithm.

30. The non-transitory software product data recording media of claim 26 , further comprising the step of:

iii) measuring light reflection from said log surface portion to generate corresponding reflected light intensity image data; and

iv) comparing with a predetermined intensity threshold the reflected light intensity data to provide a further indication of the residual bark in addition to said resulting data.

31. The non-transitory software product data recording media of claim 30 , wherein said measuring step iii) includes correcting said light intensity image data to compensate for the generally curved shape of said log surface.

32. The non-transitory software product data recording media of claim 30 , further comprising the step of:

v) generating from the resulting data a two-dimensional image representing areas of said log surface respectively characterized by said detected fiber loss, said detected residual bark, and a detected roughness value lower than a predetermined roughness threshold.