Abstract: A multi-scale normalized cut algorithm bases on anti-symmetrical bi-orthogonal wavelet transform is proposed to address the problems that blur and noise occurred in the image of Micro-electronic components for industrial inspection site. Firstly, multi-scale edge detection of the anti-symmetrical bi-orthogonal wavelet is used to extract the contours with smoothing and denoising. Then, according to constraint matrix. edge contours and strength values can obtain a weight matrix after decomposition of the wavelet of image. Finally, the eigenvectors of the image are extracted easily using the spectral segmentation techniques, and the segmentation result is obtained after discretization. To test the effectiveness of the introduced scheme, the image segmentation tests are carried out for the circuit board component and partial fault images which are captured from Industrial micro-scopes and PASCAL VOC2012 segmentation database, then comparison on Precision, Recall, F-measure, Mean Absolute Error and time expenditure are performed among the proposed approach, the normalized cut method, multiscale Ncut scheme, min-cut/max-flow algorithms and constrained parametric min-cuts. Experimental results demonstrate that the introduced method yields better segmentation quality than these four algorithms.