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YILDIZ, KAZIM

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YILDIZ

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2015 - 20172
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Author: YILDIZ, KAZIM × Subject: ADAPTIVE WAVELETS ×

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Now showing 1 - 2 of 2
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    PublicationOpen Access
    Wavelet transform and principal component analysis in fabric defect detection and classification
    (PAMUKKALE UNIV, 2017) BULDU, ALİ; Yildiz, Kazim; Buldu, Ali
    Fabric defects are determined by quality control.staff in textile industry, This process cannot be performed objectively and it constitutes both time and cost difficulties, In this study the cashmere and denim lubric images which ure used often in textile industry ure tried in both detection and classification process. Quality control machine prototype has been manufactured then defected fabric images were obtained with the help of thermal imaging. The fabric defects were detected and classified by using the thermal images, Averagely 95% classification accuracy has been achieved on experiments for two different fabric types. According to the experimental results, the fabric quality control process can be muck after the drying and fixing, without any further quality control step.
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    PublicationMetadata only
    A novel thermal-based fabric defect detection technique
    (TAYLOR & FRANCIS LTD, 2015) BULDU, ALİ; Yildiz, Kazim; Buldu, Ali; Demetgul, Mustafa; Yildiz, Zehra
    During the fabric production process, many defects can be occurred stemming from the unevenness in spinning, weaving, finishing processes, or from the raw materials. The fabric quality control process for the detection of these defects is carried out by specialist operators. In this paper, a new method based on the use of thermal camera for detecting these defects from the textile fabric images is presented. For identification process of defective area, fabric images were obtained by a thermal camera during the fabric flow in quality control machine that was specially designed for this experiment. Defective and defect-free regions on fabric surface were determined by thermal camera due to the thermal differences. The mentioned thermal defect detection system will eliminate the worker usage for fabric quality control process, thus it will provide a cost-effective and competitive manufacturing.