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      <JournalTitle>International Journal of Engineering, Science and</JournalTitle>
      <Volume-Issue>Volume 6, Issue 3</Volume-Issue>
      <Season>July 2017</Season>
      <ArticleType>Engineering, Science and Mathematics</ArticleType>
          <FirstName>P K</FirstName>
      <Abstract>Quality control is one of the basic issues in textile industry. Texture analysis plays an important role in automated visual inspection of texture images to detect their defects. The investment in an automated fabric defect detection system is more than economical when reduction in labor cost and associates benefits are considered. The inspection of real fabric defects is particularly challenging due to the large number of fabric defect classes, which are characterized by their vagueness and ambiguity. Many fabric defects are very small, which makes them very difficult to detect by only monitoring intensity change. Faultless fabric is a repetitive and regular global texture and Fourier transform can be applied to monitor the spatial frequency spectrum of the fabric. When the defect occurs in the fabric, its regular structure is changed so that the corresponding intensity at some specific positions of the frequency spectrum would change. In this paper, a simulated fabric model is used to understand the relationship between the fabric structure in the image space and in the frequency space. Based on the three dimensional frequency spectrums, two significant spectrum diagrams are defined and used for analyzing the fabric defect. These two diagrams are called the central spatial frequency spectrums. The defects are broadly classified into 3 classes. Double yarn, missing yarn and web or broken fabric. After evaluating these 3 classes of defects using some simulated models and real samples, seven characteristics parameters for central spatial frequency are computed.</Abstract>
        <Abstract>https://ijesm.co.in/ubijournal-v1copy/journals/abstract.php?article_id=3165&amp;title=DEFECT DETECTION IN TEXTURE BY FOURIER ANALYSIS APPROACH</Abstract>