Lumber inspection method, device and program

• US 8,253,793 B2
• Filed: 04/20/2007
• Issued: 08/28/2012
• Est. Priority Date: 04/20/2007
• Status: Active Grant

• Current Assignee: Meinan Machinery Works, Inc.
• Original Assignee: Meinan Machinery Works, Inc.
• Inventors: Hiraoka, Noriyuki
• Primary Examiner(s): Maung, Zarni
• Application Number:
  US12/596,211
• Publication Number:
  US 20100141754A1
• Time in Patent Office: 1,957 Days
• Field of Search: 348 91- 93
• US Class Current: 348/92
• CPC Class Codes: B27G 1/00 Machines or devices for removing knots or other irregularities or for filling-up holes filling up cracks or holes in a veneer cutting block B27L5/00; caulking decks B63B5/065
• CPC Class Codes: G01J 3/46 Measurement of colour; Colour measuring devices, e.g. colorimeters measuring colour temperature G01J5/60
• CPC Class Codes: G01J 3/462 Computing operations in or between colour spaces; Colour management systems
• CPC Class Codes: G01J 3/50 using electric radiation detectors
• CPC Class Codes: G01N 21/8986 Wood
• CPC Class Codes: G01N 33/46 Wood
• CPC Class Codes: G06T 2207/10024 Color image
• CPC Class Codes: G06T 2207/30161 Wood; Lumber
• CPC Class Codes: G06T 7/001 using an image reference approach
• CPC Class Codes: G06T 7/90 Determination of colour characteristics

Abstract

An imaging means captures a color image of lumber. An image processing means obtains the color distribution of the color image captured by the imaging means, compares the obtained color distribution with a predetermined color distribution of normal lumber, judges the obtained color distribution as an abnormal one when it is deviated from the color distribution of normal lumber by a predetermined value or more, and detects a defect of the lumber having the abnormal color distribution deviated by a value larger than the predetermined value in an area on the surface of the lumber captured by the imaging means.

Claims

1. A lumber inspection method executed by a programmed processor, comprising:

obtaining a color image of lumber captured by imaging means;

obtaining a color distribution of the color image captured by the imaging means;

comparing the obtained color distribution with a predetermined color distribution of normal lumber;

judging the obtained color distribution as an abnormal one when it is deviated from the color distribution of normal lumber by a predetermined value or more; and

detecting an area on the surface of the lumber captured by the imaging means whose abnormal color distribution has a value greater than the predetermined value as a defect of the lumber.

2. The lumber inspection method according to claim 1, wherein when setting, as an inspection object, lumber whose defective area is small relative to an inspection object area, image distributions acquired on a per-inspection object basis are replaceably used from case to case as the predetermined color distributions of normal lumber.

3. The lumber inspection method according to claim 1, wherein an abnormal brightness portion is detected by obtaining a brightness histogram of the color distribution of the captured color image.

4. The lumber inspection method according to claim 3, characterized in that, for the brightness histogram of the color distribution of normal lumber determined in advance, an entire normal distribution is estimated from a cumulative frequency of a partial region on the assumption that an entire distribution follows a normal distribution.

5. The lumber inspection method according to claim 2, wherein an abnormal brightness portion is detected by obtaining a brightness histogram of the color distribution of the captured color image.

6. A lumber inspection device comprising:

an imaging unit for capturing a color image of lumber; and

an image processing unit for obtaining a color distribution of the color image captured by the imaging unit, comparing the obtained color distribution with a predetermined color distribution of normal lumber, judging the obtained color distribution as an abnormal one when it is deviated from the color distribution of normal lumber by a predetermined value or more, and detecting an area on the surface of the lumber captured by the imaging unit whose abnormal color distribution has a value greater than the predetermined value as a defect of the lumber.

7. The lumber inspection device according to claim 6, wherein when setting, as an inspection object, lumber whose defective area is small relative to an inspection object area, the image processing unit replaceably uses image distributions acquired on a per-inspection object basis from case to case as the predetermined color distributions of normal lumber.

8. The lumber inspection device according to claim 6, wherein the image processing unit detects an abnormal brightness portion by obtaining a brightness histogram of the color distribution of the captured color image.

9. The lumber inspection device according to claim 8, wherein, for the brightness histogram, the image processing unit estimates an entire normal distribution from a cumulative frequency of a partial region on the assumption that an entire distribution follows a normal distribution.

10. The lumber inspection device according to claim 7, wherein the image processing unit detects an abnormal brightness portion by obtaining a brightness histogram of the color distribution of the captured color image.

11. A computer-readable storage device storing a program for causing a computer to function as:

an imaging unit for capturing a color image of lumber; and

an image processing unit for obtaining a color distribution of the color image captured by the imaging unit, comparing the obtained color distribution with a predetermined color distribution of normal lumber, judging the obtained color distribution as an abnormal one when it is deviated from the color distribution of normal lumber by a predetermined value or more, and detecting an area on the surface of the lumber captured by the imaging unit whose abnormal color distribution has a value greater than the predetermined value as a defect of the lumber.