Mrmrf-based Texture Classiication
نویسندگان
چکیده
In this paper, we present a new scheme to classify diierent textures. We propose a scheme to use wavelet decomposition with Markov random eld modeling to classify textures which we called mul-tiresolution MRF(MRMRF). The parameters of each Markov random eld models combined with wavelet energy signatures are used as features in texture classiication. The classiier here we use is nearest linear combination(NLC). Our experiments show that NLC is better than NN classiier. Thus we can analyze the textures with Markov Random Field models on diierent scales with the wavelet decomposition eeectively.
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