In this paper a multiscale wavelet-based algorithm for matching stand-alone shapes is developed. The algorithm uses the Dyadic Wavelet Transform (DWT) to decompose a shape's boundary into multi-scale levels. Featu...
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ISBN:
(纸本)0769521274
In this paper a multiscale wavelet-based algorithm for matching stand-alone shapes is developed. The algorithm uses the Dyadic Wavelet Transform (DWT) to decompose a shape's boundary into multi-scale levels. Features are extracted by calculating the curve moment invariants of the approximation coefficients. If the measured dissimilarity is small, then the shapes are globally similar Local similarily is investigated by calculating the normalized cross correlation of the 1-D triangle area representation of the detail coefficients. The presented algorithm not only finds similar shapes, but it also can easily distinguish between seemingly similar shapes. The algorithm is invariant to the affine transformation and to the starting point variation of the shape contour.
One of the problems in image processing is finding an appropriate threshold in order to convert an image to a binary one. In this paper we introduce a new method for image thresholding. We use reinforcement learning a...
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ISBN:
(纸本)0769521274
One of the problems in image processing is finding an appropriate threshold in order to convert an image to a binary one. In this paper we introduce a new method for image thresholding. We use reinforcement learning as an effective way to find the optimal threshold. Q (A) is implemented as a learning algorithm to achieve more accurate results. The reinforcement agent uses objective rewards to explore/exploit the solution space. It means that there is not any experienced operator involved and the reward and punishment function must be defined for the agent. The results show that this method works successfully and can be trained for any particular application.
Many image watermarking schemes against geometric attacks have been proposed. Rotation, scaling, translation (Rst) invariant image watermarking based on log-polar mapping (LPM) and Radon transform is one of them. In t...
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ISBN:
(纸本)0769521274
Many image watermarking schemes against geometric attacks have been proposed. Rotation, scaling, translation (Rst) invariant image watermarking based on log-polar mapping (LPM) and Radon transform is one of them. In this paper, we analyze the embedding and detection process of the above-mentioned method. We focus on how to select the watermark data, how to embed the watermark into the original image, and how to implement approximative inverse log-polar mapping (ILPM) during the embedding process. We analyze watermark detection when a watermarked image is scaled or rotated, and propose to use the rotation rectification to battle rotation. Three detection methods are compared.
One of the most important steps in digital mammography is an adequate segmentation of possible abnormalities. This obviously minimizes errors in further stages such as in classification. However, several factors affec...
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ISBN:
(纸本)0769521274
One of the most important steps in digital mammography is an adequate segmentation of possible abnormalities. This obviously minimizes errors in further stages such as in classification. However, several factors affect the proper segmentation of mammograms. Mammograms contain low signal to noise ratio (low contrast) and a complicated structured background. In this article we are describing a generic approach for detecting patterns of architectural distortions in mammograms that is both complete and uncommitted to any type of training. Our detection algorithm dynamically updates the pixels intensities by following their neighboring transition zone. Such approach proved to be effective for detecting the edges of all types of breast abnormalities including the stellate.
Range image segmentation has many applications in computervision areas such as computer graphics and robotic vision. A generic methodology for 3D point set analysis in which planar structures play an important role i...
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ISBN:
(纸本)0769521274
Range image segmentation has many applications in computervision areas such as computer graphics and robotic vision. A generic methodology for 3D point set analysis in which planar structures play an important role is defined. It consists mainly of a specific K-means algorithm which is able to process different shapes in cluster. At the same time, within geometric and topologic considerations, a set of application-driven heuristics is designed. This helps to find out the right number of structures in point sets in order to give a good visualization and representation of a large scale environment without a priori models. Our aim is to propose a simple and generic frame for 3D scene understanding. Tests were realised on different types of environment data: natural and man-made. This research project has been realized with EADS (French Air Space Society). Keywords: Fuzzy clustering, 3D reconstruction and scene analysis, range image segmentation, environment modeling, stereovision.
We present a system that detects people in indoor scenes by modeling the motion history of foreground blobs, rather than their shape or appearance. The system tracks all foreground blobs over time with a multi-hypothe...
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ISBN:
(纸本)0769521274
We present a system that detects people in indoor scenes by modeling the motion history of foreground blobs, rather than their shape or appearance. The system tracks all foreground blobs over time with a multi-hypothesis tracker, and considers a blob to be a person if it exhibited sufficient autonomous movement in the course of its tracking history. This way, people can be correctly classified even if they are seen in a wide range of body poses, if they remain still for a long time, or if they change appearance by taking off a coat. Evaluation on over 1h of video demonstrated good performance for both heuristic and decision tree based classification.
Given a standard RGB color image, an approach to recovering the shading image, an intrinsic image that depends only on the geometry of the viewing situation, is presented. The approach is formulated for scenes that ex...
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ISBN:
(纸本)0769521274
Given a standard RGB color image, an approach to recovering the shading image, an intrinsic image that depends only on the geometry of the viewing situation, is presented. The approach is formulated for scenes that exhibit both diffuse and specular properties. It is discriminative in the sense that variations in intensity caused by material changes are first detected and then removed. Material changes are detected using a method based on color information alone. The method stems from a scheme proposed here to handle specularities under known scene illumination chromaticity. This scheme is also used to produce an image that is free of specular reflections. Any material changes are then removed from this specular-free image by using an inpainting technique. The performance of the proposed approach has been tested on synthetic images.
Previous methods for estimating the motion of an observer through a static scene require that image velocities can be measured For the case of motion through a cluttered 3D scene, however, measuring optical flow is pr...
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ISBN:
(纸本)0769521274
Previous methods for estimating the motion of an observer through a static scene require that image velocities can be measured For the case of motion through a cluttered 3D scene, however, measuring optical flow is problematic because of the high density of depth discontinuities. This paper introduces a method for estimating motion through a cluttered 3D scene that does not measure velocities at individual points. Instead the method measures a distribution of velocities over local image regions. We show that motion through a cluttered scene produces a bowtie pattern in the power spectra of local image regions. We show how to estimate the parameters of the bowtie for different image regions and how to use these parameters to estimate observer motion. We demonstrate our method on synthetic and real data sequences.
In this paper, a boundary detection algorithm based on conflicting strength between edge and boundary in SAR (synthetic aperture radar) sea ice images is presented. In SAR sea ice images, different ice types can have ...
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ISBN:
(纸本)0769521274
In this paper, a boundary detection algorithm based on conflicting strength between edge and boundary in SAR (synthetic aperture radar) sea ice images is presented. In SAR sea ice images, different ice types can have the same intensity signature but the floe size and shape can be different. To measure the flow size and shape, proper boundary detection is crucial. Due to the inherent speckle noise with SAR satellite images, boundary detection in SAR images can be challenging. The implemented technique eliminates the unwanted edges from the overestimated boundary to obtain the desired boundaries by measuring the strength of each edge and the boundaries to which it belongs. Edges are removed if edge strength does not conflict with the boundary strength. Test results using operational SAR sea ice imagery are presented and results are encouraging.
This paper presents a perceptual organization based method for the representation and extraction of junction structures of edge segments from digital images. Perceptual Junctions (PJs) are higher-level view invariant ...
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ISBN:
(纸本)0769521274
This paper presents a perceptual organization based method for the representation and extraction of junction structures of edge segments from digital images. Perceptual Junctions (PJs) are higher-level view invariant feature entities, which are made up by intersected generic edge tokens including both linear and non-linear segments. The class of low-order PJs (LPJs) is the junctions defined by two connected segments, and detected directly by an edge tracking and partitioning algorithm. The class of high-order PJs (HPJs) is the junctions made up by more than two segments which are extended from LPJs by grouping additional segments from different edge traces. The method is robust since it mainly uses qualitative perceptual features. The computation is efficient because it is mainly involved in symbolic reasoning. The experimental results are provided.
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