چکیده (انگلیسی):

Recently, the research towards Brodatz database for texture classification done at considerable amount of
study has been published, the effective classification are vulnerable towards for training and test sets. This
study presents the novel texture classification method based on feature descriptor, called spatial cooccurrence
with discrete shearlet transformation through the LPboosting classification. It can be considered
as a frame through the texton template that mapped into the texture images and it works directly on relating
the adjacent spatial with its pixel boundary through the local intensity order. Hence, the proposed method
for the feature extraction and classification of texture suggested with the experimentation through the spatial
co-occurrence matrix with the power spectrum based discrete shearlet transform and it classified through
the LP boosting method on Brodatz database images. This hybrid second order statistical based
classification method significantly outperforms the existing texture descriptors the multiscale geometric tool
shows the proposed method outperforms other classification method.