Fabric Defect Detection Using Discrete Curvelet Transform
Dr Shubhangi D.C
, Gangambika
GLCM, Discrete Curvelet Transform
With the growing demand of customers for cloth range in the fashion industry, texture of the fabric becomes much more numerous, which brings pleasant challenges to accurate identification of fabric discoveries. Also included was a comparative study of the wavelet-based, GLCM-based curvelet-based techniques. The high precision obtained through the expected technique indicates an economical fabric defect resolution. Note that this study is that the initial recorded arrangement to explore the probabilities of a brand new multi-resolution analytical method called digital curvelet transform to address the material defect problem. Using "Discrete Curvelet Transform," the recognizer acquires digital fabric images by means of image acquisition tool and transforms the image into binary image. In MATLAB the algorithmic rule suggested is simulated. The performance of the proposed model for detection of defects was assessed through in-depth experiments with varied types of real samples of cloth.
"Fabric Defect Detection Using Discrete Curvelet Transform", IJSDR - International Journal of Scientific Development and Research (www.IJSDR.org), ISSN:2455-2631, Vol.5, Issue 7, page no.471 - 474, July-2020, Available :https://ijsdr.org/papers/IJSDR2007067.pdf
Volume 5
Issue 7,
July-2020
Pages : 471 - 474
Paper Reg. ID: IJSDR_192143
Published Paper Id: IJSDR2007067
Downloads: 000347183
Research Area: Engineering
Country: Gulbarga, Karnataka, India
ISSN: 2455-2631 | IMPACT FACTOR: 9.15 Calculated By Google Scholar | ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 9.15 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
Publisher: IJSDR(IJ Publication) Janvi Wave
