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We present a new approach to facial expression recognition, which uses Wavelet for reducing the high dimensional data of facial expression images into a relatively low dimension data and then uses K nearest neighbor(KNN) as the classifier for the expression classification afterwards. In Existing System, uses Stochastic Neighbor Embedding (SNE) for reducing the high dimensional data of facial expression...
To detect landslides by object-based image analysis using criteria based on shape, color, texture, and, in particular, contextual information and process knowledge, candidate segments must be delineated properly. This has proved challenging in the past, since segments are mainly created using spectral and size criteria that are not consistent for landslides. This paper presents an approach to select...
In this paper, we investigate the applicability of Electrocardiogram (ECG) signals for human identification. Wavelet Transform (WT) and Independent Component Analysis (ICA) methods are applied to extract morphological features that appear to offer excellent discrimination among subjects. The proposed method is aimed at the two-lead ECG configuration that is routinely used in long-term continuous monitoring...
ECG signal provides a dynamic assessment of the cardiac activities. To analyze the ECG signal, some innovative ECG delineation techniques along with a few known techniques were used to provide the optimum strategy for marking of events. The techniques were applied on 125 records of CSE DS-3 database for calibration and subsequently, on the data acquired from no known-cardiac Cobra bitten patients...
In this study we propose a new system to detect and correct red eye defect in images. The proposed system works in three phases namely face localization, eye localization and red eye removal. Face localization involves method for extracting face from the image. Eye localization locates eye in the face extracted. The red eye defect, if present, is automatically detected and corrected using a simple...
Currently, radiologists indicate the femur endpoints with an interactive marker device; however, these measurements are subjective and have proved to be inconsistent. The main objective of this work is to obtain a time-efficient morphology-based algorithm to recognize femur contour in fetal ultrasound images, refine its shape for automatic length measurement, and thus, attaining accuracy and reproducibility...
In this paper, we propose unconstrained handwritten Kannada character recognition based on Fisher linear discriminant analysis (FLD). The proposed system extracts features from well known FLD, Two dimensional FLD (2D-FLD) and diagonal FLD. In order to classify the characters, we explore different distance measure techniques and compare their results. The proposed system is tested on unconstrained...
This paper presents a SVM based computer-aided diagnosis (CAD) system for the characterization of clustered microcalcifications in digitized mammograms. First, the region of interest (ROI) in mammogram is enhanced using morphological enhancement (MORPHEN) method. Second, pixels in potential microcalcification regions are segmented out by using edge detection and morphological operations. Third, features...
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