This paper introduces a human body contour registration method for static pedestrian images with unconstrained background. By using a statistical compound model to impose structural and textural constraints on valid pedestrian appearances, the matching process is robust to image clutter. Experimental results show that the proposed method register pedestrian contours in complex background effect...

Speckle is an inherent characteristic of tissues when assessed by ultrasound. De-speckling is performed to improve the visualization of anatomical details but the information encoded in speckle is often discarded. In this paper we propose an ultrasonic decomposition procedure which estimates despeckled and speckle images starting with images created from Radio Frequency (RF) data. These images ...

The SAR and SAS images are perturbed by a multiplicative noise called speckle, due to the coherent nature of the scattering phenomenon. The use of speckle reduction filters is necessary to optimize the image exploitation procedures. This paper presents a new denoising method in the wavelet domain, which tends to reduce the speckle, preserving the structural features (like the discontinuities) a...

The monitoring, fault detection and visualization of defects are a strategic issue for product quality. This paper presents a novel methodology based on the integration of textural Multivariate image analysis (MIA) and multivariate statistical process control (MSPC) for process monitoring. The proposed approach combines MIA and p-control charts, as well as T 2 and RSS images for defect location...

Age related macular degeneration (AMD) is an eye related disease which leads to blindness as the disease progresses. Hence it is important to detect the disease early for timely treatment. This paper discusses about the identification of macular degeneration using multiresolution techniques and texture analysis from the fundus images of the eye. Images are analyzed at different scales and resol...

We present a method to integrate case-based reasoning (CBR) with object-oriented image classification to classify SPOT images. Images were first segmented into discrete objects at multiple scales. CBR was then used to classify these objects by comparing their geometric shapes, spectral characteristics, and textural measurements with those of the past objects prepared from archived SPOT images a...

PURPOSE A novel approach to a computer aided diagnosis system for the Parkinson's disease is proposed. This tool is intended as a supporting tool for physicians, based on fully automated methods that lead to the classification of (123)I-ioflupane SPECT images. METHODS (123)I-ioflupane images from three different databases are used to train the system. The images are intensity and spatially no...

Rapid assessment of tissue biopsies is a critical issue in modern histopathology. For breast cancer diagnosis, the shape of the nuclei and the architectural pattern of the tissue are evaluated under high and low magnifications, respectively. In this study, we focus on the development of a pattern classification system for the assessment of breast cancer images captured under low magnification (...

Lung cancer, one of the leading causes of cancer-related deaths, usually appears as solitary pulmonary nodules (SPNs) which are hard to diagnose using the naked eye. In this paper, curvelet-based textural features and clinical parameters are used with three prediction models [a multilevel model, a least absolute shrinkage and selection operator (LASSO) regression method, and a support vector ma...