JOURNAL ARTICLE

Fabric defect detection based on projected transform for feature extraction

Abstract

In order to resolve the key technology problem of automated fabric defect detection, projected transform is proposed to extract features of the fabric image making use of fabric characteristic in this paper. Automated fabric defect detection scheme is divided into two phases, which are the study phase and the detection phase. During the study phase, features of normal fabric image are extracted to get the feature data set of normal fabric. During the detection phase, the method of anomaly detection is developed using features of fabric image to detect defect. Testing on general fabric by this method, experimental results demonstrate that each of feature values is in the normal range for normal fabric image, and one feature value at least is abnormal for defective fabric image. Defects can be located according to the location of abnormal value.

Keywords:
Feature extraction Feature (linguistics) Artificial intelligence Pattern recognition (psychology) Image (mathematics) Computer vision Computer science Feature detection (computer vision) Phase (matter) Anomaly detection Image processing Physics

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FWCI (Field Weighted Citation Impact)
4
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0.18
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Topics

Industrial Vision Systems and Defect Detection
Physical Sciences →  Engineering →  Industrial and Manufacturing Engineering
Image Processing Techniques and Applications
Physical Sciences →  Engineering →  Media Technology
Image and Object Detection Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition

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