For target tracking,automatic target recognition and detection applications,they value edge detection sensibility,precision and location accuracy rather than other *** at these three criterions,this paper presents an ...
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ISBN:
(纸本)9781479970186
For target tracking,automatic target recognition and detection applications,they value edge detection sensibility,precision and location accuracy rather than other *** at these three criterions,this paper presents an edge detection algorithm based on matched ***,a matched filter was designed by analyzing the edge model for natural image,then the edge response was computed using the designed matched filter;secondly,the lower and discontinuous filtered responses were further suppressed using a dedicated one-dimension filter;finally,the edge image was obtained by binarizing the edge response with a local adaptive *** results illustrate that the proposed algorithm has more improvement than the Sobel and Canny operators in detection sensibility,precision and location ***,the algorithm can be implemented with parallel pipeline using FPGA,so it is also rather suitable for real-time applications.
The use of mathematical morphology in low- and mid-level imageprocessing and computervision applications has allowed the development of a class of techniques for analyzing shape information in color images. These te...
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The goal of this paper is twofold. First, we present a supervised fuzzy c-mean (SFCM) classifier for the classification of high dimensional data. Comparisons with conventional FCM clustering technique and Bayesian cla...
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This paper proposes a new analytical method for estimating parameters of a homogeneous isotropic Potts model with an asymmetric Gibbs potential function. The model is generalized by including both pairwise and triple ...
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Magnetic resonance imaging (MRI) intensity inhomogeneities can be attributed to imperfections in the RF coils or some problems associated with the acquisition sequences. The result is a slowly varying shading artifact...
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In this paper, we propose a hybrid Tabu Expectation Maximization (TEM) Algorithm for segmentation of Brain Magnetic Resonance (MR) images in both supervised and unsupervised framewrok. Gaussian Hidden Markov Random Fi...
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In this chapter, an image inpainting approach based on l 1-norm regularization is presented for the estimation of pixels corrupted by the random-valued impulse noise. It is a two-stage reconstruction scheme. First, a ...
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Presents a fast, six degrees of freedom, registration technique to accurately locate the position and orientation of medical volumes (e.g. CT, MRI) with respect to each other for the same patient. The technique uses s...
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Barcode capturing using embedded camera in mobile phone is prone to producing images with out of focus blurring. Barcode decoding systems usually fail to decode barcodes from an image that is affected by image blurrin...
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Compressed sensing in magnetic resonance imaging (CS-MRI) improves the MRI scan time by acquiring only a few k-space samples and then reconstructs the image using a nonlinear procedure from the highly undersampled mea...
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