Fabric Defect Detection Using a One-class Classification Based on Depthwise Separable Convolution Autoencoder

Detection of Fake Accounts in Social Networks Based on One Class Classification

Detection of fake accounts on social networks is a challenging process. The previous methods in identification of fake accounts have not considered the strength of the users’ communications, hence reducing their efficiency. In this work, we are going to present a detection method based on the users’ similarities considering the network communications of the users. In the first step, similarity ...

Fabric Defect Detection Based on Computer Vision

Broken ends, missing picks, oil stain and holes are the most common fabric defects. To deal with the situation that manual fabric detection will affected by the subjective factors of inspectors, an automatic computer vision based fabric defect detection method is introduced in this paper. The system uses threshold segmentation method to identify if there are any defects existed in the fabric, a...

Fabric Defect Detection Using Homogeneity

Fabric defect detection algorithm based on local neighborhood is proposed to improve the accuracy and real-time of Fabric defect detection. A local neighborhood window moves over the entire inspection image. For homogeneity measurethe coefficient of variation is used. A defect-free region will generate a smaller value of Variation Coefficient than that of a defective region. To extract and segm...

Discriminative fabric defect detection using adaptive wavelets

Fabric defect detection using adaptive wavelet

This paper studies the adaptive wavelet design for fabric defect detection. In order to achieve translation invariance and more flexible design, the wavelet design focused on nonsubsampled wavelet transform. We design the wavelet filters under the constraints that the analysis filters are power complementary, and the wavelet has only one vanishing moment, which corresponds to a multiscale edge ...