Pixel Classification by Divergence-Based Integration of Multiple Texture Methods and Its Application to Fabric Defect Detection

作者: Miguel Angel Garcia , Domènec Puig

DOI: 10.1007/978-3-540-45243-0_18

关键词:

摘要: This paper presents and evaluates a pixel-based texture classifier that integrates multiple feature extraction methods through new scheme based on the Kullback J-divergence. Experimental results show proposed technique yields qualitatively better image segmentations than well-known both supervised unsupervised classifiers specific families of methods. A practical application to fabric defect detection is presented.

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