Abstract:

The features of the defects image of wood veneer are analyzed, an algorithm of veneer knot defect inspection is proposed which based on extension of C-V model and AOS scheme coupling with filling background. Firstly, improved a new level set approach for image segmentation which was proposed by Chan-Vese based on Mumford-Shah, the algorithm could increase the speed of segmentation. Secondly, the approach used AOS scheme, which is unconditional stable, to discrete the level set function. Finally, coupling with the technique of background make a new image which reduced the different characteristics between the target and background. Contrast experimental results show that, this method can fast inspect single knot defect, reveal this coupling method has better segmentation effect than C-V method and improving method. Using multiple level sets as the initial contours of curve evolution, experimental results show that this method could also quickly inspect the image of veneer multi-knot defect and achieve the mutli-object segmentation of veneer knot.

Key words: veneer knot defect image, extended C-V model, AOS scheme, multi-object segmentation, technique of painting background