A method is proposed based on the combination of wavelet analysis and principal component analysis (PCA). Microcalcification (MC) candidate regions are initially labeled using area and contrast criteria. Mallat’s redundant dyadic wavelet transform is used to analyze the frequency content of image patterns at horizontal and vertical directions. PCA is used to efficiently encode MC patterns in wa...

| In this paper we propose two feature extraction techniques, termed DCT-mod and DCT-delta, for use in an illumination invariant face based identity veri cation system. We compare the performance of the proposed techniques against two standard methods: Principal Component Analysis (PCA) and the 2-D Discrete Cosine Transform (DCT). Experiments on the VidTIMIT database support the use of the prop...

This paper compares and discusses four techniques for model order reduction based on compressed sensing (CS), less relevant basis removal (LRBR), principal component analysis (PCA) and partial least squares (PLS). CS and PCA have already been used for reducing the order of power amplifier (PA) behavioral models for digital predistortion (DPD) purposes. While PLS, despite being popular in some s...

With the increasing of non-linear, burst or un-balanced load, power quality issues in the grid is becoming important. With more power quality monitors installed with higher sampling rates, an expanded size of power quality data brings difficulty to storage, transmission and analysis. In this paper, principal component analysis (PCA), which is a popular feature extraction algorithm in pattern re...

In this project you will explore the use of Principle Component Analysis (PCA) and Probabilistic PCA (PPCA). PPCA is closely-related to factor analysis, which is described in chapter 14 of your text. Our application is face recognition, following on the work of Moghadden and Pentland. A minimum version of this project would involve reading chapter 14 and conducting a face recognition experiment...

Data processing and management is common now a days. In this paper, automatic processing of forms written in Kannada language is considered. A suitable pre-processing technique is presented for extracting handwritten characters. Principal Component Analysis (PCA) and Histogram of oriented Gradients (HoG) are used for feature extraction. These features are fed to multilayer feed forward back pro...

This work explores image processing techniques that involve the application of eigenspace methods for pose detection. An eigenspace method for data compression used in the image processing field is commonly referred to as Principal Component Analysis (PCA). We present some recently introduced eigenspace concepts for detecting the pose angle of an occluded object located in an image containing b...