A Comparative Study of Filter Based Texture Operators Using Mahalanobis Distance
نویسندگان
چکیده
Texture feature extraction operators, which comprise linear filtering, eventually followed by post-processing, are considered. The filters used are Laws’ masks, filters derived from well-known discrete transforms, and Gabor filters. The post-processing step comprises non-linear point operations and/or local statistics computation. The performance is measured by means of the Mahalanobis distance between clusters of feature vectors derived from different textures. The results show that post-processing improve considerably the performance of filter based texture operators.
منابع مشابه
Identifying Useful Variables for Vehicle Braking Using the Adjoint Matrix Approach to the Mahalanobis-Taguchi System
The Mahalanobis Taguchi System (MTS) is a diagnosis and forecasting method for multivariate data. Mahalanobis distance (MD) is a measure based on correlations between the variables and different patterns that can be identified and analyzed with respect to a base or reference group. MTS is of interest because of its reported accuracy in forecasting small, correlated data sets. This is the type o...
متن کاملAnalysis of motor fan radiated sound and vibration waveform by automatic pattern recognition technique using “Mahalanobis distance”
In recent years, as the weight of IT equipment has been reduced, the demand for motor fans for cooling the interior of electronic equipment is on the rise. Sensory test technique by inspectors is the mainstream for quality inspection of motor fans in the field. This sensory test requires a lot of experience to accurately diagnose differences in subtle sounds (sound pressures) of the fans, and t...
متن کاملApplying the Mahalanobis-Taguchi System to Vehicle Ride
The Mahalanobis Taguchi System is a diagnosis and forecasting method for multivariate data. Mahalanobis distance is a measure based on correlations between the variables and different patterns that can be identified and analyzed with respect to a base or reference group. The Mahalanobis Taguchi System is of interest because of its reported accuracy in forecasting small, correlated data sets. Th...
متن کاملAn Evaluation of Mahalanobis-Taguchi System and Neural Network for Multivariate Pattern Recognition
The Mahalanobis-Taguchi System is a diagnosis and predictive method for analyzing patterns in multivariate cases. The goal of this study is to compare the ability of the Mahalanobis- Taguchi System and a neural-network to discriminate using small data sets. We examine the discriminant ability as a function of data set size using an application area where reliable data is publicly available. The...
متن کاملMahalanobis-Taguchi System-based criteria selection for strategy formulation: a case in a training institution
The increasing complexity of decision making in a severely dynamic competitive environment of the universe has urged the wise managers to have relevant strategic plans for their firms. Strategy is not formulated from one criterion but from multiple criteria in environmental scanning, and often, considering all of them is not possible. A list of criteria utilizing Delphi was selected by consu...
متن کامل