To improve the accuracy of image matching shoeprint image feature matching method based on PCA-SIFT is proposed. Firstly, feature detection and pre-matching of images are done by using PCA-SIFT (principal component analysisscale invariant feature transform) algorithm. And then, the correlation coefficient is used as similarity measurement, which can filter image interest points. By this method,...

Texture is a rich source of visual information about the surface characteristics of an object in the digital image. So texture characteristics play an important role in texture image classification. In this paper, we propose a novel approach of texture image classification based on nonsubsampled contourlet transform (NSCT) and local directional binary patterns (LDBP). The NSCT has translation i...

q-mode hierarchical cluster (hca) and principal component analysis (pca) were simultaneously applied to groundwater hydrochemical data from the three times in 2004: june, september, and december, along the ain azel aquifer, algeria, to extract principal factors corresponding to the different sources of variation in the hydrochemistry, with the objective of defining the main controls on the h...

functional magnetic resonance imaging (fmri) is a safe and non-invasive way to assess brain functions by using signal changes associated with brain activity. the technique has become a ubiquitous tool in basic, clinical and cognitive neuroscience. this method can measure little metabolism changes that occur in active part of the brain. we process the fmri data to be able to find the parts of br...

In this study, a multi objective optimization for end milling of Al 6061 alloy has been presented to provide better surface quality and higher Material Removal Rate (MRR). The input parameters considered for the analysis are spindle speed, depth of cut and feed. The experiments were planned as per Taguchis design of experiment, with L27 orthogonal array. The Grey Relational Analysis (GRA) has b...

An automated system is used for fast human face recognition. The 2DFLD algorithm is tested on the various databases. PCA algorithm is tested on various databases. As the face system is totally nonintrusive, existing security of face recognition system are more effective without bothering the user in any way. The 2DFLD approach is compared with the standard PCA. The 2DFLD is used for recognizing...

Principal Component Analysis (PCA) has many different important applications especially in pattern detection such as face detection / recognition. Therefore, for real time applications, the response time is required to be as small as possible. In this paper, new implementation of PCA for fast face detection is presented. Such new implementation is designed based on cross correlation in the freq...

Background Various clinical (disease activity, seropositive RA etc.) and metabolic risk factors (Dkk1 have been associated with erosive rheumatoid arthritis (RA). However, such might be intertwined, multicollinearity reduce our ability to discern the individual contribution score. Principal component analysis (PCA) is statistical technique for reducing dataset’s dimension principal regression (...

We introduce algorithms and architectures for automatic spike detection and alignment that are designed for low power. Some of the algorithms are based on principal component analysis (PCA). Others employ a novel integral transform analysis and achieve 99% of the precision of a PCA detector, while requiring only 0.05% of the computational complexity. The algorithms execute autonomously, but req...