Top-Hat Transform Sequence Analysis and Application in Automatic Detection of Products Defects

Abstract

Defects in parts bring great harms.To implement automatic monitoring of parts quality,images of parts are processed and analyzed.A method of Top-Hat transform sequence analysis is proposed.Firstly,iterative open operation and Top-Hat transformation of the signal are computed by using size driven structure elements and the O-TH(Open-TopHat) decomposition tree is obtained.Objects analysis spectrum is established whose amplitude is the energy of the O-TH tree leaf nodes.Then,the optimum size of the structure element and the optimum segmentation threshold are obtained by analyzing the behavior of each object of the signal in the spectrum.Thus,all the targets in the signal are located accurately.On this basis,the preliminary segment result is patched by comparing the elements in the TH sequence with the Top-Hat transform result which uses the optimum structure element,and the targets in the signal are detected completely.Finally,object extraction algorithm based on Top-Hat transform sequence analysis is designed.The method is verified by experiments including several kinds of parts and different defects.The results prove that the method has good generality and strong immunity and anti-background interference abililty,high accuracy in defect extraction and good robustness.