Image Batik Classification Based using Ensemble Learning

Mulaab Mulaab


Automatic feature descriptor is substantial part of component  in the textural image retrieval  and  classification.  Image  batik  has  its  unique  pattern  characteristic  such  as  color intensity,  ornament  visualisation  and  ornament  size.  In  motive  of  batik  classificatin  rneed feature  extraction  methods.  The  scale  invariant  feature  transform  (SIFT  )  can  be  used  for  feature descriptor in some applications. In this paper, we presents an efficient based on Bag of Words  (BoW)  with  features  of  scale  invariant  feature  transform  and  ensemble  classifier  for improving classification accuracy.

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