Color texture classification using adaptive discrete multiwavelets transform

الملخص EN

The classification of textures images has attracted the attention of many researchers.

The multiscale techniques for gray level texture analysis have been intensively studied.

In this paper, we aim on extending texture classification of color images by using the multiwavelets transform, a new notion addition to wavelet.

The recognition of textures deals with both feature extraction and classification phases.

In the classification phase the evolutionary computation techniques (genetic programming) was used for more speed recognition result evaluation.

In our experiment results the proposed method has achieved 99.6 % test accuracy on an average.

In addition, the experimental results also show that classification rules generated by this approach are robust to some noises on textures.