spectral decomposition of time series has a significant role in seismic data processing and interpretation. since the earth acts as a low-pass filter, it changes frequency content of passing seismic waves. conventional representing methods of signals in time domain and frequency domain cannot show time and frequency information simultaneously. time-frequency transforms upgraded spectral decompo...

This paper describes a new method for analysis and segmentation of facial laser range data employing complex–valued non–orthogonal Gabor wavelets, principal component analysis and a topological mapping network. The initial data set consisting of shape and texture information is encoded in amplitude and phase of a complex 2D image function. A set of oriented Gabor filters performs a decompositio...

Individual identification and behavioural analysis of pigs is a key link in the intelligent management piggery, for which computer vision technology based on application improvement deep learning model has become mainstream. However, operation high requirements to hardwares, also weak interpretability, make it difficult adapt both mobile terminals embedded applications. In this study, first put...

Nowadays, Multimodal biometrics has created a substantial interest in the field of identification management due to higher recognition performance. This paper presents a comparative analysis of different fusion levels like feature level, score level and decision level in multimodal biometrics using fingerprint and face. Histogram of Oriented Gradients (HOG) descriptor has been used for fingerpr...

In this paper, two-dimensional principal component analysis (2DPCA) is used for image representation and recognition. Compared to 1D PCA, 2DPCA is based on 2D image matrices rather than 1D vectors so the image matrix does not need to be transformed into a vector prior to feature extraction. Instead, an image covariance matrix is constructed directly using the original image matrices, and its ei...

Biometric performance improvement is a challenging task. In this paper, a hierarchical strategy fusion based on multimodal biometric identification systems is presented. This strategy relies on a combination of several biometric traits using a multi-level biometric fusion hierarchy. The multi-level biometric fusion includes a pre-classification fusion with optimal feature selection and a post-c...

A major problem in text categorization is the high dimensionality of feature vector space, which is about ten thousands in common. To reduce the dimensionality of the space while keeping the categorization accuracy is useful for improving categorization effectiveness and applying new categorization algorithms. Current feature selection methods for text categorization are partially effective in ...