A system which integrates an ultrasonic sensor and an off-the-shelf charge coupled device camera sensor was constructed and tested. An active method which requires no complex scene analysis was designed to search for ...
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A system which integrates an ultrasonic sensor and an off-the-shelf charge coupled device camera sensor was constructed and tested. An active method which requires no complex scene analysis was designed to search for targets efficiently within a single captured image under uncontrolled background conditions. Detailed three dimensional positions of targets are estimated from their corresponding two dimensional image coordinates in the integrated system. Invariant features of targets combined with neural network approach are used to identify various bar targets even when their two dimensional projection of cross section are varying and distorted when seen from different viewpoints.
We have presented a novel shape signature based on the histogram of the distance of the contour pixels from its barycentre. Such signature is obviously rotation invariant and proves to be robust with respect to random...
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We have presented a novel shape signature based on the histogram of the distance of the contour pixels from its barycentre. Such signature is obviously rotation invariant and proves to be robust with respect to random noise and very sensitive to small local deformations of the shape. Indeed it seems an appropriate strategy for shape quality control applications also from the computational point of view.
A novel vision system is proven at a conceptual level to help unmanned remotely operated vehicles (ROV's) interpret underwater oceanic scenes and clarify noisy image sequences. images contain objects of interest (...
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A novel vision system is proven at a conceptual level to help unmanned remotely operated vehicles (ROV's) interpret underwater oceanic scenes and clarify noisy image sequences. images contain objects of interest (metal cylinders of a known oil rig structure) and background (water). After contrast stretching for enhancement, images are segmented using a quickly convergent method based on Markov Random Fields (MRF's). this iterated conditional mode MRF uses deterministic relaxation to rapidly converge. Cylinders are analysed to determine the camera's viewing direction, range and twist off the vertical. the camera's position is then calculated given knowledge of the node in view. Successive viewpoints from a sequence of images are fed through a Kalman filter to predict the next viewpoint. Placing this in a 3D computer model of the structure allows a 2D predicted image to be projected. this is combined withthe next acquired image to improve object recognition by the MRF segmentation method. this novel predictive feedback method shows better resilience to noise, matching noisy images to the clearer model that would otherwise go unrecognised.
this paper deals with recognition of complex shape and the method used is based on minimization of prior knowledge. We study both representations of image features and object shapes linked to photometry and geometry p...
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this paper deals with recognition of complex shape and the method used is based on minimization of prior knowledge. We study both representations of image features and object shapes linked to photometry and geometry properties. A fuzzy representation is used which is defined by independent membership functions of geometric distortion, such as rotation, zoom and deformations due to the complexity of natural objects. this method is applied in two problems: automatic fish sorting and face recognition, where objects are complex for being real-world images.
this paper proposes a method of edge representation which is more general than the conventional edge representation method. While the localization of conventional edges is considered as the problem of determining its ...
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this paper proposes a method of edge representation which is more general than the conventional edge representation method. While the localization of conventional edges is considered as the problem of determining its existence at a certain location, that is, either 0 (non-edge) or 1 (an edge point), our representation method defines the location as some measure of plausibility of edges using the fuzzy set theory. thus, if the location of intensity edges is unclear, or if the intensity function is different from ideal edge models, the degree of edgeness and location is represented as a fuzzy membership value. the conventional edge is a special case of our representation-a case where the input intensity is almost same as the model of edges (for example, a step function) with little degradation or noise. We show a computation model of our fuzzy edge representation method followed by experimental results.
We present a conceptual framework acid a process model for feature extraction and iconic visualization. the features are regions of interest extracted from a dataset: they are represented by attribute sets, which play...
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We present a conceptual framework acid a process model for feature extraction and iconic visualization. the features are regions of interest extracted from a dataset: they are represented by attribute sets, which play a key role in the visualization process. these attribute sets are mapped to icons, or symbolic parametric objects, for visualization. the features provide a compact abstraction of the original data, and the icons are a natural way to visualize them. We present generic techniques to extract features and to calculate attribute sets, and describe a simple but powerful modeling language which was developed to create icons and to link the attributes to the icon parameters. We present illustrative examples of iconic Visualization created withthe techniques described, showing the effectiveness of this approach.
An adaptive scheme is introduced to detect and track moving targets under multiscenario environment including target in complex background, target is partial obstructed and multi- target or multi-bait. the performance...
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ISBN:
(纸本)0819421375
An adaptive scheme is introduced to detect and track moving targets under multiscenario environment including target in complex background, target is partial obstructed and multi- target or multi-bait. the performance modeling is important to do withthe fact that it can enhance the ability to predict the target tracking system performance in scenarios where data is not available. A critical use of performance models is selecting proper algorithms and adaptation of algorithm parameters to meet different scenarios' changes. the performance model is built at algorithm level instead of system level. For each algorithm, its performance model was built based upon experimental design. Some image metrics are employed to describe scene variation, and integrated into performance model. In our experiments, withthe controls of adaptive controller of our system based on algorithm performance model and expert knowledge, system can select proper algorithms, tune algorithm parameters, and target was tracked perfectly in total 400 frames.
In this paper, we develop a static global scheduling scheme for mapping computervision and image procesaing (CVIP) operations on distributed-memory multiprocessors. the scheduler operates on task graphs containing li...
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the paper presents a general non-rigid body representation for physically-based modeling of dynamic behaviour of heterogeneous objects and its application in a development of a new heterogeneous morphing technique to ...
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Telesensation is a concept of combination of virtual reality and telecommunications. through it, an image of a scene from nature or an image of a museum exhibit from a remote place is instantly transmitted over high s...
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