In addition, the task of target defect identification for one defective image can be accomplished within 3 s by the proposed system.
Such defective image pairs can cause a weakened depth sense in the observer, and it can even result in headache or nausea when exposed for a long time.
The effects of such defective image pairs on human visual system [3, 6 8] and some quality assessment methods based on disparities [9] have been investigated in recent years.
Sections lost in the sectioning or immunostaining process can effectively be replaced by interpolation of an adjacent image with the defective image to average and fill in the missing data computationally.
Experimental results, carried out by real defective images provided by a LCD manufacturer, indicate that the proposed F-SVDD ensemble not only greatly improves the performance of SVDD, but also outperforms other commonly used classifiers such as support vector machine (SVM), in terms of target defect identification rate.
Figure 6 Diffusion results of the radiographic images: (a1, a2) defective radiographic images; (b1, b2) respective diffusion results using the P-M model; (d1, d2) respective diffusion results using the Shin-Du model; (f1, f2) respective diffusion results using the proposed model; (c1, c2), (e1, e2), (g1, g2) thresholding results using Otsu method.
Values were eliminated if they were flagged as M (spot was identified to be defective through image inspection at manufacturing), C (spot has a high level of background contamination), I (spot has an irregular shape), or S (spot has a high number of saturated pixels).
In developing the scheme, the Gabor filters are designed on the basis of the texture features extracted optimally from a non-defective fabric image by using a Gabor wavelet network (GWN).
IPC-7 is rather a defective material, and TEM images show different types of defects in the material.
The experiment results show that, with the aid of penalized least squares, the defective regions in thermal images are characterized more clearly, while the signal-to-noise ratio (SNR) values are increased significantly.
Unlike some existing detection algorithms which concentrate on the characteristics of defects with an active search way, the proposed method removes the non-defective areas of the image passively at the same time of image processing, which reduces a large amount of computation.
