- AURUM Mühendislik Sistemleri ve Mimarlık Dergisi
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- BROKEN STITCH DETECTION METHOD FOR SEWING OPERATION USING CNN FEATURE MAP AND IMAGE-PROCESSING TECHN...
BROKEN STITCH DETECTION METHOD FOR SEWING OPERATION USING CNN FEATURE MAP AND IMAGE-PROCESSING TECHNIQUES
Authors : Timur İNAN, Samah Noaman Sahi SAHI
Pages : 217-233
Doi:10.53600/ajesa.1374410
View : 30 | Download : 50
Publication Date : 2023-12-31
Article Type : Research
Abstract :Quality in industrial processes has become increasingly important and cost reduction and process optimization are becoming increasingly necessary Quality control brings increased production and even increased profits for a process. It can be said, then, that it is the most important metric when it comes to production. It is extremely difficult to have a 100% defect-free manufacturing process. One of the industrial processes that has received such attention regarding defects is the weaving process. The present work will make a global study on Machine Learning techniques and also on Wavelets. This study may serve as a basis for future academic work. The application built in the present work will also serve as an example of how a computer vision system can vary from the classifier algorithm used to the feature extraction technique, which in this case, will use the Wavelet Transform. In this work we Survey the state of the art in methods of recognizing defects in fabrics. We will also Create the database, as well as the set of images to be used. Extract information from the image with the Wavelet Transform. Test different classification algorithms in order to find the best answer for this problem. Improve the performance of the classifier algorithms through the CNN algorithm. Validate the system using the k-fold cross validation technique.Keywords : CNN, DL, CL, WT