منابع مشابه
Fingerprint classification using an AM-FM model
Research on fingerprint classification has primarily focused on finding improved classifiers, image and feature enhancement, and less on the development of novel fingerprint representations. Using an AM–FM representation for each fingerprint, we obtain significant gains in classification performance as compared to the commonly used National Institute of Standards system, for the same classifier.
متن کاملA comparative study on AM and FM features
In this paper, we investigate the advantages of frequency modulation (FM) features by conducting speech recognition experiments and statistical analysis. The importance of temporal aspects in speech recognition has been discussed along with the importance of amplitude modulation (AM) and frequency modulation. Recently, we have proposed a speech recognition system that is based on the combinatio...
متن کاملComparison of AM-FM based features for robust speech recognition
Effective feature extraction for robust speech recognition is a widely addressed topic and currently there is much effort to invoke non-stationary signal models instead of quasi-stationary signal models leading to standard features such as LPC or MFCC. Joint amplitude modulation and frequency modulation (AM-FM) is a classical non-parametric approach to nonstationary signal modeling and recently...
متن کاملSpeaker Identification using FM Features
The AM-FM modulation model of speech is a nonlinear model that has been successfully used in several branches of speech-related research. However, the significance of the AM-FM features extracted from this model has not been fully explored in applications such as speaker identification systems. This paper shows that frequency modulation (FM) features can improve speaker identification accuracy....
متن کاملAutomatic Classification of Normal and Cancer Lung CT Images Using Multiscale AM-FM Features
Computer-aided diagnostic (CAD) systems provide fast and reliable diagnosis for medical images. In this paper, CAD system is proposed to analyze and automatically segment the lungs and classify each lung into normal or cancer. Using 70 different patients' lung CT dataset, Wiener filtering on the original CT images is applied firstly as a preprocessing step. Secondly, we combine histogram analys...
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ژورنال
عنوان ژورنال: International Journal of Smart Sensor and Adhoc Network.
سال: 2011
ISSN: 2248-9738
DOI: 10.47893/ijssan.2011.1018