the proceedings contain 40 papers. the topics discussed include: a simple framework for natural animation of digitized models;application-independent accurate mouse placements on surfaces of arbitrary geometry;color m...
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ISBN:
(纸本)0769529968
the proceedings contain 40 papers. the topics discussed include: a simple framework for natural animation of digitized models;application-independent accurate mouse placements on surfaces of arbitrary geometry;color mathematical morphology based on partial ordering of spectra;new tensorial representation of color images: tensorial morphological gradient applied to color image segmentation;two-stage binary image operator design: an approach based on interaction information;seed-relative segmentation robustness of watershed and Fuzzy connectedness approaches;an exact and efficient algorithm for the orthogonal art gallery problem;robust and adaptive surface reconstruction using partition of unity implicits;data hiding for binary documents robust to print-scan, photocopy and geometric distortions;improved reversible mapping from color to gray;and rotation-invariant and scale-invariant steerable pyramid decomposition for texture image retrieval.
the identification and classification of motion patterns in point trajectories has been an important issue in understanding and representing dynamic scenes. this paper proposes an unsupervised approach to identify coh...
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ISBN:
(纸本)9780769529967
the identification and classification of motion patterns in point trajectories has been an important issue in understanding and representing dynamic scenes. this paper proposes an unsupervised approach to identify coherent motion in video. Instead of producing a spatio-temporal segmentation of the raw data, the proposed method analyzes point trajectories along the video sequence to identify sets of points that move coherently. this new way of extracting motion information from videos potentially can be used in different areas of imageprocessing and computer vision.
Medical image registration is a difficult problem. Not only a registration algorithm needs to capture both large and small scale image deformations, it also has to deal with global and local image intensity variations...
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ISBN:
(纸本)9780769529967
Medical image registration is a difficult problem. Not only a registration algorithm needs to capture both large and small scale image deformations, it also has to deal with global and local image intensity variations. In this paper we describe a new multiresolution elastic image registration method that challenges these difficulties in image registration. To capture large and small scale image deformations, we use both global and local affine transformation algorithms. To address global and local image intensity variations, we apply an image intensity standardization algorithm to correct image intensity variations. this transforms image intensities into a standard intensity scale, which allows highly accurate registration of medical images.
this paper proposes a new Tensorial Representation of HSI color images, where each pixel is a 2 X 2 second order tensor, that can be represented by an ellipse. A proposed tensorial morphological gradient (TMG) is defi...
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ISBN:
(纸本)9780769529967
this paper proposes a new Tensorial Representation of HSI color images, where each pixel is a 2 X 2 second order tensor, that can be represented by an ellipse. A proposed tensorial morphological gradient (TMG) is defined as the maximum dissimilarity over the neighborhood determined by a structuring element, and is used in the watershed segmentation framework. Many tensor dissimilarity functions are tested and other color gradients are compared. the comparison uses a new methodology for qualitative evaluation of color image segmentation by watershed, where the watershed lines of the n most significant regions are overlaid on the original image for visual comparison. Experiments show that the TMG using Frobenius norm dissimilarity function presents superior segmentation results, in comparison to other tested gradients.
Stack filters are a special case of non-linear filters. they have a good performance for filtering images with different types of noise while preserving edges and details. A stack filter decomposes an input image into...
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ISBN:
(纸本)9780769529967
Stack filters are a special case of non-linear filters. they have a good performance for filtering images with different types of noise while preserving edges and details. A stack filter decomposes an input image into several binary images according to a set of thresholds. Each binary image is filtered by a Boolean function. the Boolean function that characterizes an adaptive stack filter is optimal and is computed from a pair of images consisting of an ideal noiseless image and its noisy version. In this work the behavior of adaptive stack filters is evaluated for the classification of Synthetic Aperture Radar (SAR) images, which are affected by speckle noise. Withthis aim it was carried out experiment in which simulated and real images are generated and then filtered with a stack filter trained with one of them. the results of their Maximum Likelihood classification are evaluated and then are compared withthe results of classifying the images without previous filtering.
this paper proposes a new rotation-invariant and scale-invariant representation for texture image retrieval based on Steerable Pyramid Decomposition. By calculating the mean and standard deviation of decomposed image ...
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ISBN:
(纸本)9780769529967
this paper proposes a new rotation-invariant and scale-invariant representation for texture image retrieval based on Steerable Pyramid Decomposition. By calculating the mean and standard deviation of decomposed image subbands, the texture feature vectors are extracted. To obtain rotation or scale invariance, the feature elements are aligned by considering either the dominant orientation or dominant scale of the input textures. Experiments were conducted on the Brodatz database aiming to compare our approach to the conventional Steerable Pyramid Decomposition, and a recent proposal for texture characterization based on Gabor Wavelets with regard to their retrieval effectiveness. Results demonstrate the superiority of the proposed method in rotated and scaled image datasets.
Optical microscopic images, especially with a nonconfocal microscope, are fundamentally limited because the optical transfer function (the Fourier transform of the point-spread function) is zero over a region of the s...
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ISBN:
(纸本)9780769529967
Optical microscopic images, especially with a nonconfocal microscope, are fundamentally limited because the optical transfer function (the Fourier transform of the point-spread function) is zero over a region of the spatial-frequency domain. Iterative algorithms were developed for the restoration and extrapolation of diffraction-limited imagery. In this paper we present the effectiveness of an iterative method based on the Richardson-Lucy algorithm for image restoration and a simultaneous modified version of Gerchberg-Papoulis method to extrapolate the spectrum and control the noise amplification. Good convergence stabilization results were achieved and also good numerical results were observed.
A good shape descriptor is necessary for automatically identifying landmarks on boundaries. Our method of boundary shape description is based on the notion of c-scale, which is a new local scale concept, defined at ea...
ISBN:
(纸本)9780769529967
A good shape descriptor is necessary for automatically identifying landmarks on boundaries. Our method of boundary shape description is based on the notion of c-scale, which is a new local scale concept, defined at each boundary element. From this representation we can extract special points of interest such as convex and concave corners, straight lines, circular segments, and inflection points. the results show that this method gives a complete description of shape and allows the automatic positioning of mathematical landmarks, which agree with our intuitive ideas of where landmarks may be defined. this method is applicable to spaces of any dimensionality, although we have focused in this paper on 2D shapes.
the choice of a color model is of great importance for many computer vision algorithms. However, there are many color models available;the inherent difficulty is how to automatically select a single color model or, al...
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ISBN:
(纸本)9780769529967
the choice of a color model is of great importance for many computer vision algorithms. However, there are many color models available;the inherent difficulty is how to automatically select a single color model or, alternatively, a subset of features from several color models producing the best result for a particular task. To achieve proper colors components selection, in this paper, it was proposed the use of wrapper method, a data mining approach, to obtain repeatability and distinctiveness in segmentation process. the result was compared with neural network method and yields good feature discrimination. the method was verified experimentally with 108 images from Amsterdam Library of Objects images (ALOI) and 10 aerial images with different photometric conditions. Furthermore, it has shown that the color model selection scheme provides a proper balance between color invariance (repeatability) and discriminative power (distinctiveness).
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