Gabor filtering is a widely adopted technique for texture analysis. The design of a Gabor filter bank is a complex task. In texture classification, in particular, Gabor filters show a strong dependence on a certain number of parameters, the values of which may significantly affect the outcome of the classification procedures. Many different approaches to Gabor filter design, based on mathematical and physiological consideration, are documented in literature. However, the effect of each parameter, as well as the effects of their interaction, remain unclear. The overall aim of this work is to investigate the effects of Gabor filter parameters on texture classification. An extensive experimental campaign has been conducted. The outcomes of the experimental activity show a significant dependence of the percentage of correct classification on the smoothing parameter of the Gabor filters. On the contrary, the correlation between the number of frequencies and orientations used to define a filter bank and the percentage of correct classification appeared to be poor.
Evaluation of the effects of Gabor filter parameters on texture classification
BIANCONI, Francesco;
2007
Abstract
Gabor filtering is a widely adopted technique for texture analysis. The design of a Gabor filter bank is a complex task. In texture classification, in particular, Gabor filters show a strong dependence on a certain number of parameters, the values of which may significantly affect the outcome of the classification procedures. Many different approaches to Gabor filter design, based on mathematical and physiological consideration, are documented in literature. However, the effect of each parameter, as well as the effects of their interaction, remain unclear. The overall aim of this work is to investigate the effects of Gabor filter parameters on texture classification. An extensive experimental campaign has been conducted. The outcomes of the experimental activity show a significant dependence of the percentage of correct classification on the smoothing parameter of the Gabor filters. On the contrary, the correlation between the number of frequencies and orientations used to define a filter bank and the percentage of correct classification appeared to be poor.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.