Check Detection and Characterization in Veneer

Qualifying with use of Digital Image Analysis

Bartosz PAŁUBICKI, Laurent BLÉRON, Jean-Claude BUTAUD, Rémy MARCHAL

ParisTech Cluny, LaBoMaP

Rue Porte de Paris

71250 Cluny, France

IUFRO – All-Division 5 ConferenceTaipei, Taiwan Oct. 29 to Nov. 2, 2007‧

What are the lathe checks?

Contents

• Introduction

• Hardware setup

• Goal

• Check detection algorithm details

• Sotfware interface

•Summary

Introduction

HardwareVision System

Hardware Setup Recomendations

•Hard image analysis for wood – different colors, inhomogeneity, light dispersing

•Hardware setup very important -> high quality of image, high contrast

•Repetability (environmental light independent, stabillzed voltage)

Goal

Succesful check measurement depends on both:

•Good quality image (good hardware settings) and

•Efficient algorithm for digital image analysis

Goal: To provide an efficient algorithm for

automatic detection of the lathe checks basing on the veneer image

Check detection algorithm

START

LOAD IMAGE

SHRINKED IMAGE ORIGINAL IMAGE

TRESHOLD

DEPTH OF SEARCHSELECTION

ROI DETERMINATION(BOUNDARIES)

EXTRACT ROI

COARSE POSITIONOF CHECKS

TRESHOLD

CLOSE PARTICLES(JOIN IF CLOSE

ENOUGH)

REMOVE SMALL PARTICLES

LABEL PARTICLES

CHOOSE PARTICLES BEING CHECKS

DETECT POSITION OF CHECKS BOTTOMS

STATISTICS ON CHECKS INTERVASL AND DEPTHS

OVERLAY RESULTS ON THE FINAL IMAGE

DETAILSSELECTION

SHRINKAGECOEFFICIENT

TRESHOLDMETHOD

START

LOAD IMAGE

SHRINKED IMAGE ORIGINAL IMAGE

TRESHOLD

ROI DETERMINATION(BOUNDARIES)

EXTRACT ROI

SHRINKAGECOEFFICIENT

Region Of Interest - CPU Time Saving

10

20

50

START

LOAD IMAGE

SHRINKED IMAGE ORIGINAL IMAGE

TRESHOLD

DEPTH OF SEARCHSELECTION

ROI DETERMINATION(BOUNDARIES)

EXTRACT ROI

COARSE POSITIONOF CHECKS

SHRINKAGECOEFFICIENT

Coarse Check Positions

D

H

START

LOAD IMAGE

SHRINKED IMAGE ORIGINAL IMAGE

TRESHOLD

DEPTH OF SEARCHSELECTION

ROI DETERMINATION(BOUNDARIES)

EXTRACT ROI

COARSE POSITIONOF CHECKS

TRESHOLD

CLOSE PARTICLES(JOIN IF CLOSE

ENOUGH)

DETAILSSELECTION

SHRINKAGECOEFFICIENT

TRESHOLDMETHOD

Checks Tracking

Option:Very low details

Option:Normal details

START

LOAD IMAGE

SHRINKED IMAGE ORIGINAL IMAGE

TRESHOLD

DEPTH OF SEARCHSELECTION

ROI DETERMINATION(BOUNDARIES)

EXTRACT ROI

COARSE POSITIONOF CHECKS

TRESHOLD

CLOSE PARTICLES(JOIN IF CLOSE

ENOUGH)

REMOVE SMALL PARTICLES

LABEL PARTICLES

CHOOSE PARTICLES BEING CHECKS

DETAILSSELECTION

SHRINKAGECOEFFICIENT

TRESHOLDMETHOD

Option:Very low details

Option:Normal details

Check Labeling

START

LOAD IMAGE

SHRINKED IMAGE ORIGINAL IMAGE

TRESHOLD

DEPTH OF SEARCHSELECTION

ROI DETERMINATION(BOUNDARIES)

EXTRACT ROI

COARSE POSITIONOF CHECKS

TRESHOLD

CLOSE PARTICLES(JOIN IF CLOSE

ENOUGH)

REMOVE SMALL PARTICLES

LABEL PARTICLES

CHOOSE PARTICLES BEING CHECKS

DETECT POSITION OF CHECKS BOTTOMS

STATISTICS ON CHECKS INTERVASL AND DEPTHS

OVERLAY RESULTS ON THE FINAL IMAGE

DETAILSSELECTION

SHRINKAGECOEFFICIENT

TRESHOLDMETHOD

Check Enumarating

Software Interface

• Effective algorithm for lathe check detection has been presented

• Few parameters possible to adjust if necessary

• Output: lathe checks intervals and depths

Summary

Wood

Thank You

CLUNY