Fabric Defect Detection Using Modified Local Binary Patterns

Fabric Defect Detection Using Modified Local Binary Patterns

Local binary patterns (LBPs) are one of the features which have been used for texture classification. In this paper, a method based on using these features is proposed for fabric defect detection. In the training stage, at first step, LBP operator is applied to an image of defect free fabric, pixel by pixel, and the reference feature vector is computed. Then this image is divided into windows a...

Defect Detection in Repetitive Fabric Patterns

In this paper a automated analysis system for defect detection in the print process of flocked fabrics with repetitive patterns is presented. This process represents a less computationally complex method than the detection of any type of pattern in the print process. For this reason, this problem can be solved using a personal computer (PC) inspecting 100% of the production that fulfill the req...

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...

Diagnosis of Tempromandibular Disorders Using Local Binary Patterns

Background: Temporomandibular joint disorder (TMD) might be manifested as structural changes in bone through modification, adaptation or direct destruction. We propose to use Local Binary Pattern (LBP) characteristics and histogram-oriented gradients on the recorded images as a diagnostic tool in TMD assessment.Material and Methods: CBCT images of 66 patients (132 joints) with TMD and 66 normal...

Discriminative fabric defect detection using adaptive wavelets