| Título: | An Enhancement over Texture Feature Based Multiclass Image Classification under Unknown Noise |
| Autores: |
Ajay Kumar Singh; MITS University Laxmangarh, Sikar, (Raj.) V P Shukla; MITS University Laxmangarh, Sikar, (Raj.) Shamik Tiwari; MITS University Laxmangarh, Sikar, (Raj.) S R Biradar; MITS University Laxmangarh, Sikar, (Raj.) |
| Fecha: | 2013-10-13 |
| Publicador: | BRAIN: Broad Research in Artificial Intelligence and Neuroscience |
| Fuente: |
 |
| Tipo: | |
| Tema: |
Artificial Intelligence, Computer Vision statistical texture, feature extraction, pattern recognition, multiclass classification, neural network |
| Descripción: | In this paper we deal with classification of multiclass images using statistical texturefeatures with two approaches. One with statistical texture feature extraction of the whole image, another with feature extraction of image blocks. This paper presents an experimental assessment of classifier in terms of classification accuracy under different constraints of images. This paper examined classification accuracy of multiclass images without noise, with some unknown noise and after filtering of noise using feed forward neural network. Results shows that blocking of image improves the performance of classifier. |
| Idioma: | Inglés |
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