Defect detection based on two different algorithms of analysis and comparison

Fabric defect detection has been an active area of research since a long time and still a robust system is needed which can fulfill industrial requirements. A robust automatic fabric defect detection system (FDDS) would results in quality products and more revenues. Many different approaches and method have been tried to implement FDDS. This paper presents a new scheme for automated FDDS implementation using Hilbert-Huang Transform (HHT) and also compares it with O penCV approach. In my implementation of both approaches in same environment, the HHT approach produces higher defect detection accuracies than OpenCV approach and more computationally efficient. The article is divided into four parts, the first part is the introduction of t wo methods, the second part for the two methods defect detection system implementation, the third pa rt is the results and the discussion of two methods, the fourth part is the conclusion. HHT is used to deal with nonlinear and non-stationary signal, the method of its adaptive is good, can be used to analyze all kinds of signals. Compared with the Fourier transform, the HHT has more explicit time- frequency description; filter performance is even more acute. In addition, its implementation is simple and can be real-time calculation. Therefore, for the engineering application and theory research, HHT has very important significance. HHT method has two parts: Empirical mode decomposition and Hilbert spectrum analysis.