Novel transform domain formulations and implementations of PCA techniques will be given. It will be shown that this new approach results in considerable computational and storage savings while yielding very high accuracy. Useful applications such as Facial and Automatic Target Recognition are given confirming the considerable performance improvement. Key-Words: Transform Domain Techniques, Prin...

This paper presents a comparative analysis of a new unsupervised PCA-based technique for steel plates texture segmentation towards defect detection. The proposed scheme called Variance Based Component Analysis or VBCA employs PCA for feature extraction, applies a feature reduction algorithm based on variance of eigenpictures and classifies the pixels as defective and normal. While the classic P...

Computational techniques derived from digital image processing are playing a significant role in the security and digital copyrights of multimedia and visual arts. This research presents discrete M-band wavelet transform (DMWT) and cosine transform (DCT) based watermarking algorithm by incorporating the randomization and principal component analysis (PCA). The proposed algorithm is expected to ...

the field study was conducted in one district of educational-experimental forest at tehran university (kheirood-kenar forest) in the north of iran. eighty-five soil profiles were dug in the site of study and several chemical and physical soil properties were considered. these factors included: soil ph, soil texture, bulk density, organic carbon, total nitrogen, extractable phosphorus and depth ...

Case study of manufacturing of crystalline drug substance was used to see the application of Principal component analysis. Principal Component Analysis (PCA) is one of the multivariate methods of analysis and has been used widely with large multidimensional data sets. PCA involves a mathematical procedure that transforms a number of possible correlated variables into a smaller number of uncorre...

With the growth of information technology there is a greater need of high security, so biometric authentication systems are gaining importance. Face recognition is more used because it’s easy and non intrusive method during acquisition procedure. Various methods are used for facial recognition. Principal component analysis (PCA) based systems are used often. In this paper we study 4 distance me...

In this paper, an improved version of Principal Component Analysis (PCA) and Independent Component Analysis (ICA) is proposed for feature extraction to classify the ischemic beats from electrocardiogram (ECG) signal. The Fuzzy C-Means (FCM) and Genetic Algorithm (GA) is combined with PCA and ICA to extract more relevant features; the proposed methods are named as Fuzzy-Genetic based PCA (FGPCA)...

spatial patterns are useful descriptors of the horizontal structure in a plant population and may change over time as the individual components of the population grow or die out. but, whether this is the case for desert woody annuals is largely unknown. in the present investigation, the variations in spatial patterns of tribulus terrestris during different pulse events in semi-arid area of the ...

In this paper, a new face recognition system based on Wavelet transform (HWT) and Principal Component Analysis (PCA) is presented. The image face is preprocessed and detected. The Haar wavelet is used to form the coefficient matrix for the detected face. The image feature vector is obtained by computing PCA for the coefficient matrix of DWT. A comparison between the proposed recognition system ...