USING SPECTRAL ESTIMATION TECHNIQUE AND ROUGH SET CLASSIFIER OF REGULAR PATTERNED FABRIC DETECTING DEFECT
| Main Authors: | Prof. S. S. Raut.,, Prof. M. S. Biradar. |
|---|---|
| Format: | Article Journal |
| Bahasa: | eng |
| Terbitan: |
, 2015
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| Subjects: | |
| Online Access: |
https://zenodo.org/record/1471460 |
Daftar Isi:
- Fabric detection has an outstanding importance in inspection of fabric quality and defects. It works on principle of spectral estimation technique vision. it gets bonded to locate defected regions accurately. This project represented a most accepted method for patterned fabric defect detection and classification using spectral estimation technique and rough set theory. To extract the Regular pattern from the image of the patterned fabric, here use of Estimating Signal Parameter via Rotational Invariance Technique (ESPRIT) is done. In this technique the defected region i.e. the shape and location of the flawed areas are detected by comparing the pattern image and the source image also the rough set classifier is trained and tested to detect the types of defects in the patterned fabric image. Practically it is observed that this method can successfully be used to analyze & find the defects in patterned fabrics with nearly 96% success rate. This method is result oriented and better improving than previous method. https://www.ijiert.org/paper-details?paper_id=140170