The diagnostic performance of two spectral techniques (the FFT and the AR modelling) to compute Doppler spectrograms and two methods (spectrum-by-spectrum threshold and edge detection by imageprocessing. to estimate ...
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An approach to image feature extraction is proposed. Complex moments of the Gabor power spectrum are used to detect linear, rectangular, hexagonal/triangular, and other structures with very fine to very coarse resolut...
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An approach to image feature extraction is proposed. Complex moments of the Gabor power spectrum are used to detect linear, rectangular, hexagonal/triangular, and other structures with very fine to very coarse resolutions. When the method is applied to texture segmentation, good results are obtained.< >
An approach to feature extraction that eliminates binarization by extracting features directly from gray scale images is presented. It not only allows the processing.of poor quality input (e.g., low contrast, dirty im...
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An approach to feature extraction that eliminates binarization by extracting features directly from gray scale images is presented. It not only allows the processing.of poor quality input (e.g., low contrast, dirty images), but also offers the possibility of significantly lower resolution for digitization.< >
A multichannel filtering-based texture segmentation method is applied to a variety of document imageprocessing.problems: text-graphics separation, address-block location, and bar code localization. In each of these s...
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A multichannel filtering-based texture segmentation method is applied to a variety of document imageprocessing.problems: text-graphics separation, address-block location, and bar code localization. In each of these segmentation problems, the text context or bar code in the image is considered to define a unique texture. Thus, all three document analysis problems can be posed as texture segmentation problems. Two-dimensional Gabor filters are used to compute texture features. Both supervised and unsupervised methods are used to identify regions of text or bar code in the document images. The performance of the segmentation and classification scheme for a variety of document images demonstrates the generality and effectiveness of the approach.< >
A method for determining the relative view orientation of randomly acquired projections of asymmetric objects is described. It extends the projection slice theorem by determining the relative orientation of projection...
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A method for determining the relative view orientation of randomly acquired projections of asymmetric objects is described. It extends the projection slice theorem by determining the relative orientation of projections by the location of lines of intersection among the Fourier transforms of the projections in 3D Fourier space. The complete algorithm is described, and its efficacy is demonstrated using real data.< >
A physiologically motivated model of illusory contour perception is examined by simulating a neural network architecture that was tested with gray-level images. The results indicate that a model that combines a bottom...
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A physiologically motivated model of illusory contour perception is examined by simulating a neural network architecture that was tested with gray-level images. The results indicate that a model that combines a bottom-up feature aggregation strategy with recurrent processing.is best suited for describing this type of perceptual completion.< >
The author attempts to solve the structuring function decomposition problem where the structuring function refers to the gray scale structuring element. A morphologically realizable representation for the structuring ...
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The author attempts to solve the structuring function decomposition problem where the structuring function refers to the gray scale structuring element. A morphologically realizable representation for the structuring function that reduces the structuring function decomposition into a series of binary structuring element decompositions is presented. Recursive algorithms that are pipelinable for efficiently performing gray scale morphological operations are developed on the basis of proposed representation and decomposition. The results are beneficial to real-time image analysis in terms of computer architecture and software development.< >
The authors randomly sample appropriate range image points and solve equations determined by these points for the parameters of selected primitive type. From K samples they measure residual consensus to choose one set...
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The authors randomly sample appropriate range image points and solve equations determined by these points for the parameters of selected primitive type. From K samples they measure residual consensus to choose one set of sample points that determines an equation having the best fit for the largest homogeneous surface patch in the current processing.region. The residual consensus is measured by a compressed histogram method that works at various noise levels. The estimated surface patch is extracted out of the processing.region to avoid further computation. A genetic algorithm is used to accelerate the search speed.< >
A complete scheme for totally unconstrained handwritten word recognition based on a single contextual hidden Markov model (HMM) is proposed. The scheme includes a morphology- and heuristics-based segmentation algorith...
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A complete scheme for totally unconstrained handwritten word recognition based on a single contextual hidden Markov model (HMM) is proposed. The scheme includes a morphology- and heuristics-based segmentation algorithm and a modified Viterbi algorithm that searches the (l+1)st globally best path based on the previous l best paths. The results of detailed experiments for which the overall recognition rate is up to 89.4% are reported.< >
A graph-theoretic approach for image segmentation is presented. The pixels of the image are represented by the vertices of an undirected adjacency graph G. All neighboring pairs of pixels are linked by arcs with capac...
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A graph-theoretic approach for image segmentation is presented. The pixels of the image are represented by the vertices of an undirected adjacency graph G. All neighboring pairs of pixels are linked by arcs with capacities assigned to reflect the strength of an edge element between the linked vertices. Segmentation is achieved by removing arcs corresponding to selected minimum cuts of G to form mutually exclusive subgraphs such that the largest intersubgraph maximum flow is minimized. This is equivalent to partitioning the image using closed contours of edge elements, which consist mostly of strong edges. The method accurately locates region boundaries and at the same time rejects contours containing isolated strong edges. The minimum cuts in G can be computed from a partially cut-equivalent tree of G. A fast algorithm for constructing partially equivalent trees that can handle graphs with several hundred thousand vertices is developed.< >
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