In this study, efficient methods for optimal sensor placement (OSP) based on a new geometrical viewpoint for damage detection in structures is presented. The purpose is to minimize the effects of noise on the damage detection process. In the geometrical viewpoint, a sensor location is equivalent to projecting the elliptical noise on to a face of response space which is corresponding to the sens...

This paper proposes a new design of spatial FIR filter to automatically detect water level from a video signal of various river surroundings. A new approach in this report applies "addition" of frames and a "horizontal" edge detector to distinguish water region and land region. Variance of each line of a filtered video frame is used as a feature value. The water level is recognized as a boundar...

In this paper problem of edge detection in digital images is considered. Edge detection based on morphological operators was applied on two sets (brain & chest) ct images. Three methods of edge detection by applying line morphological filters with multi structures in different directions have been used. 3x3 filter for first method, 5x5 filter for second method, and 7x7 filter for third method. ...

A model based fault detection filter is developed for structural health monitoring of a simply supported beam. The structural damage represented in the plant model is decomposed and is shown to reduce to a fault direction vector maintaining a fixed direction. According to detection filter theory, this fault detection vector under certain circumstances can be uniquely detected and identified thr...

We report on a novel fiber based coherent detection system employing an optical preamplifier, a spectrum bandpass filter, and a time-domain filter. The time-domain filter, a synchronous time gate, reduces the in-band Amplified Spontaneous Emission (ASE ) beat noise, which cannot be achieved by the spectrum bandpass filter alone. In preliminary experiments with a 100 GHz bandpass filter, no degr...

Novel features and weak classifiers are proposed for face detection within the AdaBoost learning framework. Features are histograms computed from a set of spatial templates in filtered images. The filter banks consist of Intensity, Laplacian of Gaussian (Difference of Gaussians), and Gabor filters, aiming at capturing spatial and frequency properties of faces at different scales and orientation...

This paper presents novel features for face detection in the paradigm of AdaBoost algorithm. Features are multi-dimensional histograms computed from a set of rectangles in the filtered images, and they represent marginal distributions of these rectangles. The filter banks consist of intensity, Laplacian of Gaussian (Difference of Gaussians), and Gabor filters, aiming at capturing spatial and fr...

We try to answer the following set of questions: ``Is it possible to design step edge detection filters given the desired response to an input step edge signal?''; ``The method extends easily to two dimensions?'' and ``Do we improve edge detection using this method?''. Answers to these questions are given by formulating the step edge detection problem in terms of a linear first kind Fredholm in...