In the latter application, the categories were ratings of the quality of paints obtained from human experts. These quality rating categories were then used as the training samples for supervised classification of paint images using texture features obtained from multi channel Gabor filters. Farrokhnia, F., Multi-channel filtering techniques for texture segmentation and surface quality inspection , Ph.D. thesis, Computer Science Department, Michigan State University, 1990. Multi-channel filtering techniques for texture segmentation and surface quality inspection . PhD thesis, Hielipan State University, 1990.
Most documents contain graphics and images, in addition to text.
Multi-channel Filtering Techniques For Texture Segmentation and Surface Quality Inspection . Michigan State University, 1990. Figure 1 shows the MTFs of eight Gabor filters which have been used in this study. The main steps of the algorithm are given below. Filter the input image through a bank of n even symmetric Gabor filters, to obtain n filtered images.