GIET Gandhi Institute of Engineering and Technology

Gunupur, India

GIET Gandhi Institute of Engineering and Technology

Gunupur, India
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Hanmandlu M.,Indian Institute of Technology Delhi | Choudhury D.K.,GIET Gandhi Institute of Engineering and Technology | Dash S.,GIFT Gandhi Institute for Technology
International Journal of Signal and Imaging Systems Engineering | Year: 2016

This paper presents the representation of fabric texture by four features: Local Binary Patterns (LBP), Local Directional Patterns (LDP), Scale Invariant Feature Transform (SIFT) and Speeded up Robust Features (SURF). The features extracted by these approaches are used in the Fuzzy Decision Tree (FDT) to detect defects in fabrics. We employ both fuzzy Gini index and fuzzy Shannon entropy as the splitting criteria. Two membership functions: Gaussian and trapezoidal are employed for the fuzzification of the genuine and imposter scores. A stopping criterion is devised to terminate the FDT. It is found that LDP features outperform LBP, SIFT and SURF features in the classification of defects in fabrics. © Copyright 2016 Inderscience Enterprises Ltd.

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