Efficient textile recognition via decomposition of co-occurrence matrices

Textile motifs such as Batik and Songket are common native textile design throughout South East Asia, and are often imbued with cultural and spiritual meanings. However despite its cultural importance, automatic classification and retrieval work based on design motifs are not extensive. Previous work based on texture classification methods have proved successful but uses over 700 attributes. We show in this work that the number of attributes can be reduced down to 2% without significantly reducing the classification rate. This indicates that with the appropriate attribute reduction, fast recognition and classification of Batik and Songket textiles can be achieved.