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  5. Detecting fabric defects by image analysis
Details

Detecting fabric defects by image analysis

Date Issued
December 1, 1993
Author(s)
Zhang, Yixiang Frank
Advisor(s)
M. Thomason
Additional Advisor(s)
Jens Gregor
Randall R. Bresee
Permanent URI
https://trace.tennessee.edu/handle/20.500.14382/33450
Abstract

A method of detecting defects in solid-shade, unpatterned woven fabrics is described. Two types of defects are studied: knots and slabs. The proposed automatic inspection system consists of a unix workstation, video camera, frame grabber and illumination device. Fabric samples are illuminated with transmitted light. A digitized picture from the video camera is stored in the memory of the computer. The computer calculates features from the picture and classifies samples as defective or defect-free. The locations of defects are also indicated. Autocorrelation function is used to determine the size of the repeat unit in the picture. Two approaches to detecting defects, gray level statistics and morphological operations, are presented. Fabric products from a local textile mill are examples of objects for inspection.

Degree
Master of Science
Major
Computer Science
File(s)
Thumbnail Image
Name

Thesis93Z452.pdf

Size

3.53 MB

Format

Unknown

Checksum (MD5)

8ecc4594fb3c7f8e539e191dc7fde560


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