This paper presents a real-time and robust method for license plate location and recognition. After adjusting the image intensity values, an optimal adaptive threshold is found to detect car edges and then the algorithm uses morphological operators to make candidate regions. Features of each region

feature. Firstly, pre-processing and morphological filtering on the vehicle image, and extract the license plate candidate area based on the structure features of the license. Then, doing color analysis in the candidate area of HSV color space to achieve coarse location of license plate. After that, using

Abstract—This paper proposes a robust system to recognize vehicle license plate by multi-frames learning. To fast locate the position of a license plate, we adopt a morphology-based method to extract important contrast features as filters to find all possible license plate candidates after

facilitated the task of understanding complex sys-tems at cellular and molecular levels in recent years. Segmentation, an important yet dif-ficult problem, is often the first processing step following acquisition. Our team previously demonstrated that a stochastic active contour based algorithm together

RECHERCHES Elastographie par ondes de cisaillement

Abstract: Online learning initia-tives over the past decade have become increasingly comprehen-sive in their selection of courses and sophisticated in their presen-tation, culminating in the recent announcement of a number of consortium and startup activities that promise to make a university

Diese Dissertation wurde vom Cuvillier Verlag Göttingen als Buch unter ISBN 978-3-95404-019-3 veröffentlicht (www.cuvillier.de). iContents

of the drudgery involved in the mathematics to be automated. This makes it easier for the casual reader to verify the results and to explore new ideas. Many tools are good at numerical math. These tools might be used to calculate the eigenvalues of a matrix or to design a filter with a specified pass

if we retain all the principal components. In other words, we recover the original data by performing the multiplication USV T . However, if we perform a truncated SVD (using svds()) then the inverse of S (inv(S)) does not exist. The transformation that performs the filtering is non