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Defect Detection algorithm of TFT-LCD Polarizing Film using the Probability Density Function based on Cluster Characteristic
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 Title & Authors
Defect Detection algorithm of TFT-LCD Polarizing Film using the Probability Density Function based on Cluster Characteristic
Gu, Eunhye; Park, Kil-Houm;
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Automatic defect inspection system is composed of the step in the pre-processing, defect candidate detection, and classification. Polarizing films containing various defects should be minimized over-detection for classifying defect blobs. In this paper, we propose a defect detection algorithm using a skewness of histogram for minimizing over-detection. In order to detect up defects with similar to background pixel, we are used the characteristics of the local region. And the real defect pixels are distinguished from the noise using the probability density function. Experimental results demonstrated the minimized over-detection by utilizing the artificial images and real polarizing film images.
Film Defect Detection;Distribution Estimation;Gaussian Kernel;Probability Density Function;
 Cited by
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