Defect Detection Of The Rotary Cut Veneer Based On C-V Model And Wavelet Theory

This thesis introduces the detection method of lumber defects,and the research station of our and foreign country. This thesis studies on the image processing of Partial Differential Equations and the C-V model of the image segmentation.The methods of wavelet transform and Gabor filter are joined to analyse and to compare the detection of the gray and the colored image of the lumber defect. With the copmuter,the defect detection of veneer peeling is accomplished automaticaly,therfore,the labor force of the artificial defection is released or replaced,at the same time,the detection accuracy and the detection velocity are improved distinctly.lt provides the foundation of the theory and practice to the improved use ratio of the lumbe.This thesis uses C-V model to accomplish the defect segmentation of the veneer peeling,therefore,the verge outline of the knot defect is achieved. For the iterative proeess of C-V model need to re-initialize,using the signed and distent function of the energy function clears out the extra cost of the needed re-initialization of the moved bight,therefore,it may finish the segmentatiom fast.For traits of the lumber are the various kinds and the large scatter,using the skills of background filing realize the detecion area of the veneer defect to be more small.For the unique principle segmentation of the C-V model,which may produce lot of redundancy information when there is heavy and complicated noise signal and chaotic gray level distribution in the image which is waiting for separation,and the disadvantage of the short step, the wavelet transform,which can decompose the image to get more uesful information,s used,therefore,the C-V model may approach the knot defect accurately and fast.Using the reconfiguration of the wavelet transform make the result of the outline detection be easy to observe.There is more uesful information,which can lead the detection be more correct,of the colored image.Using the vector C-V model,which can adequately use the colored information of the image,detects the defect of the wood,at the same time, the Gabor filter, which can decompose the image in the perspective and various direction way,is used, therefore,more detail information is achieved and the veracity of the segementation is improved. At the same time,the recognition of the wood defect,which is with heavy and complicated texture information and chaotic color scatter is achieved.This thesis analyses the C-V model rom the Partial Differential Equations method and raises up the improved C-V model and the vector C-V model.The C-V model is improved by using the wavelet transform and the Gabor filter.lt impluses the computerization of the veneer defect.