Open AccessOverFeat Network Algorithm for Fabric Defect Detection in Textile Industry
Author(s) -
S. Kavitha,
J Manikandan
Publication year - 2021
Publication title -
journal of innovative image processing
Language(s) - English
Resource type - Journals
ISSN - 2582-4252
DOI - 10.36548/jiip.2021.4.003
Subject(s) - automation , task (project management) , process (computing) , computer science , textile , work (physics) , algorithm , textile industry , class (philosophy) , process automation system , artificial intelligence , industrial engineering , engineering , mechanical engineering , systems engineering , materials science , archaeology , composite material , history , operating system
Automation of systems emerged since the beginning of 20th century. In the early days, the automation systems were developed with a fixed algorithm to perform some specific task in a repeated manner. Such fixed automation systems are revolutionized in recent days with an artificial intelligence program to take decisions on their own. The motive of the proposed work is to train a textile industry system to automatically detect the defects presence in the generated fabrics. The work utilizes an OverFeat network algorithm for such training process and compares its performances with its earlier version called AlexNet and VGG. The experimental work is conducted with a fabric defect dataset consisting of three class images categorised as horizontal, vertical and hole defects.