Pattern recognition using higher-order local autocorrelation coefficients
نویسندگان
چکیده
منابع مشابه
Pattern recognition using higher-order local autocorrelation coefficients
The autocorrelations have been previously used as features for 1D or 2D signal classification in a wide range of applications, like texture classification, face detection and recognition, EEG signal classification, and so on. However, in almost all the cases, the high computational costs have hampered the extension to higher orders (more than the second order). In this paper we present an effec...
متن کاملRobust Feature Vector Set Using Higher Order Autocorrelation Coefficients
In this paper, a feature extraction method that is robust to additive background noise is proposed for automatic speech recognition. Since the background noise corrupts the autocorrelation coefficients of the speech signal mostly at the lower orders, while the higher-order autocorrelation coefficients are least affected, this method discards the lower order autocorrelation coefficients and uses...
متن کاملTexture Classification Using Extended Higher Order Local Autocorrelation Features
This study investigates effective image features for characterization of local regions. We propose an extension of higher order local autocorrelation (HLAC) features. The original HLAC features are restricted up to the second order. They are represented by 25 mask patterns. We increase their orders up to eight and extract the extended HLAC features using 223 mask patterns. Large mask patterns a...
متن کاملA New Scheme for Image Recognition Using Higher-Order Local Autocorrelation and Factor Analysis
This paper proposes a new scheme for multipurpose image recognition based on Higher-order Local AutoCorrelation (HLAC) features and factor analysis. First, HLAC features, which are inherently invariant under translation, computationally inexpensive, and additive, are extracted from the input images. Second, factor analysis is applied to the feature vectors so as to decompose the feature vectors...
متن کاملA Face Recognition Method Using Higher Order Local Autocorrelation And Multivariate Analysis
This paper 1 proposes a face recognition method which is characterized by structural simplicity, train-ability and high speed. The method consists of two stages of feature extractions. At rst, higher order local autocorrelation features which are shift-invariant and additive are extracted from an input image. Then those features are linearly combined on the basis of multivariate analysis method...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Pattern Recognition Letters
سال: 2004
ISSN: 0167-8655
DOI: 10.1016/j.patrec.2004.03.007