The problem of navigating a robot vehicle which on unstructured roads that have no lane markings, may have degraded surfaces and edges, and may be partially obscured by strong shadows is addressed. These conditions ca...
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ISBN:
(纸本)081862163X
The problem of navigating a robot vehicle which on unstructured roads that have no lane markings, may have degraded surfaces and edges, and may be partially obscured by strong shadows is addressed. These conditions cause many road following systems to fail. The authors have built a system, UNSCARF, which is based on patternrecognition techniques, for successfully navigating on a variety of unstructured roads. UNSCARF does not need a road location prediction to find the location of the road;therefore, UNSCARF can be used as a bootstrapping system. UNSCARF uses a clustering technique to group pixels with similar colors and locations. UNSCARF then matches models of road shape to locate the roads in the image. These methods are more robust in noisy conditions than other road interpretation techniques. UNSCARF has been integrated into a navigation system that has successfully driven a test vehicle in many types of weather conditions.
The authors present the organization of an interleaved wrap-around memory system for a partitionable parallel/pipeline architecture with P pipes of L processors each. The architecture is designed to efficiently suppor...
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ISBN:
(纸本)0818690895
The authors present the organization of an interleaved wrap-around memory system for a partitionable parallel/pipeline architecture with P pipes of L processors each. The architecture is designed to efficiently support real-time imageprocessing and computer vision algorithms, especially those requiring global data operations. The interleaved memory system makes the architecture highly scalable in that L and P can be chosen to optimize performance for particular problems and reconfigurable in that, once L and P are fixed, problems of any size can still be mapped onto the architecture. The authors demonstrate techniques and methods for mapping computational structures to the architecture by considering the case of the 1-D butterfly network (1DBN). Since many other computational structures can be mapped to 1DBN, this gives a firm application base for the architecture. The authors also demonstrate methods for scheduling and controlling the memory system.
The problem of automatically learning knowledge-directed control strategies is considered. In particular, this work addresses the problem of learning object-specific recognition strategies from object descriptions and...
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ISBN:
(纸本)0818620579
The problem of automatically learning knowledge-directed control strategies is considered. In particular, this work addresses the problem of learning object-specific recognition strategies from object descriptions and sets of interpreted training images. A separate recognition strategy is developed for every object in the domain. The goal of each recognition strategy is to identify any and all instances of the object in an image, and give the 3-D position (relative to the camera) of each instance. The goal of the learning process is to build a strategy that minimizes the expected cost of recognition, subject to accuracy constraints imposed by the user.
Template matching is concerned with measuring the similarity between patterns of two objects. A massively parallel approach to patternrecognition with a large template set is proposed. A class of imagerecognition pr...
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ISBN:
(纸本)0818620307
Template matching is concerned with measuring the similarity between patterns of two objects. A massively parallel approach to patternrecognition with a large template set is proposed. A class of imagerecognition problems inherently needs large template sets, for example, the recognition of Chinese characters, which needs thousands of templates. The proposed algorithm is based on the SIMD-SM-R machine or the SIMD machine with broadcasting abilities, which is the most popular parallel machine to date, and uses a multiresolution method to search for the matching template. The approach uses the pyramid data structure for the multiresolution representation of templates and the input imagepattern. For a given image it scans the template pyramid searching for the match. Implementation of the proposed scheme is described.
An image-matching algorithm, called the dynamic space-warping algorithm (DSWA), is presented. It is based on both local-distance diagrams and dynamic programming. The DSWA can solve space-warping problems (e.g., shrin...
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An image-matching algorithm, called the dynamic space-warping algorithm (DSWA), is presented. It is based on both local-distance diagrams and dynamic programming. The DSWA can solve space-warping problems (e.g., shrinking, enlarging, rotation, and distortion) with good performance by embedding controllable flexibility (or warping). The concept of flexibility can be explained using local-distance diagrams. With flexibility, the local-distance diagram between two two-dimensional images is four dimensional. Based on compression and expansion, DSWA generates a minimum distance from the four-dimensional local-distance diagram. Experimental results show that the DSWA is very reliable.
An adaptive-control strategy developed for multidiameter rollers is described. The method is based on microcomputer-controlled in-process size-measurement techniques. The system enables faster and more accurate roller...
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ISBN:
(纸本)081861966X
An adaptive-control strategy developed for multidiameter rollers is described. The method is based on microcomputer-controlled in-process size-measurement techniques. The system enables faster and more accurate roller grinding, replacing the skilled operator with an expert system. Stepper-motor-driven steadies and the associated computer control system are described.
A network is described that recognizes objects from uncertain image-derivable descriptions. The network handles uncertainty by making the recognition and segmentation decisions simultaneously, in a cooperative way. Bo...
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ISBN:
(纸本)0818620579
A network is described that recognizes objects from uncertain image-derivable descriptions. The network handles uncertainty by making the recognition and segmentation decisions simultaneously, in a cooperative way. Both problems are posed as labeling problems, and a coupled Markov random field (MRF) is used to provide a single formal framework for both. Prior domain knowledge is represented as weights within the MRF network and interacts with the evidence to yield a labeling decision. The domain problem is the recognition of structured objects composed of simple junction and link primitives. Implementation experiments demonstrate the parallel segmentation and recognition of multiple objects in noisy ambiguous scenes with occlusion.
A boundary descriptor called surface code is developed. It can be used as a matching feature in the process of identification of an object. The surface code generation technique was tested on both real and synthetic i...
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A boundary descriptor called surface code is developed. It can be used as a matching feature in the process of identification of an object. The surface code generation technique was tested on both real and synthetic images. The surface codes have been generated successfully for all the images studied. The results indicate that the code is orientation independent and dimension independent, in which case hierarchical information in the form of extra code elements is needed to distinguish between similar shapes of different sizes.
A postprocessing approach that uses both statistical and structural information to eliminate the false minutiae in skeleton fingerprint images is described. The attributes of fingerprint ridges are presented by statis...
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ISBN:
(纸本)0879425970
A postprocessing approach that uses both statistical and structural information to eliminate the false minutiae in skeleton fingerprint images is described. The attributes of fingerprint ridges are presented by statistics, and these attributes are used to describe the structure of the false minutiae. The proposed approach analyzes the entire minutia structures, not just in a small window, much like the way humans analyze a fingerprint pattern. To verify the effectiveness of the approach, ten processed images with different shapes were contrasted with rolled fingerprint cards. False minutiae made up 36% of the total minutiae before processing and only about 4% after processing. Moreover, the ridge separation and continuity are good throughout the fingerprint image.
A novel approach is presented for pruning the amount of search needed to match image features to object models. The technique relies on active networks which capture various visibility and geometric constraints betwee...
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ISBN:
(纸本)0818620579
A novel approach is presented for pruning the amount of search needed to match image features to object models. The technique relies on active networks which capture various visibility and geometric constraints between features of a model to prune these features from search space during matching. The networks, which can be efficiently implemented in Boolean logic, integrate harmoniously with the previous work in feature recognition and object matching. A method is proposed for clustering model features (vsets) and four types of constraints which assist in building the networks. The authors show, both analytically and empirically, the dramatic reduction in search provided by activation nets.
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