This paper reviews the curve method [6] which recovers, as special cases, the two spline methods: one with interval tension in [5]: and the other with point tension in [4]. This curve scheme has been generalized for t...
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ISBN:
(纸本)3540606971
This paper reviews the curve method [6] which recovers, as special cases, the two spline methods: one with interval tension in [5]: and the other with point tension in [4]. This curve scheme has been generalized for the designing of surfaces i.e. 3D objects (open or closed) can be captured, together with the facility of local as well as global. point and interval shape controls, with any rectangular domain.
In this paper, we present a method for analysis and 3D visualization of high-resolution 3D blood vessels images obtained by cone-beam CT. We are working toward an interactive system which exploits the recent 3D recons...
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ISBN:
(纸本)3540606971
In this paper, we present a method for analysis and 3D visualization of high-resolution 3D blood vessels images obtained by cone-beam CT. We are working toward an interactive system which exploits the recent 3D reconstruction approaches, computer graphics, and 3D image processing techniques to facilitate detailed anatomical measurement and visualize the complex blood vessels morphology. The key approaches of our system are a 3D reconstruction image from cone-beam projections, a quantitative analysis based on the blood vessels structure description, and a volume visualization for the inspection of blood vessels structures. From results of the application to a patient's blood vessels, we present the effectiveness of our system.
Thinning is a very important preprocessing step for many imageanalysis operations. The main drawbacks of traditional thinning algorithms are slow speed and serious deformation. To remedy these problems, a novel appro...
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ISBN:
(纸本)0818671289
Thinning is a very important preprocessing step for many imageanalysis operations. The main drawbacks of traditional thinning algorithms are slow speed and serious deformation. To remedy these problems, a novel approach which generates the skeleton of binary patterns via block decomposition and contour vector matching is proposed. The performance of the proposed algorithm is compared with the existing algorithm. Experimental results confirm the superiority of the new approach.
A fast handwritten wordrecognition system for real time applications is presented. Preprocessing, segmentation and feature extraction are implemented using chain code representation. Dynamic matching between each cha...
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A fast handwritten wordrecognition system for real time applications is presented. Preprocessing, segmentation and feature extraction are implemented using chain code representation. Dynamic matching between each character of a lexicon entry and segment(s) of input wordimage is used for ranking words in the lexicon. Speed of the entire recognition process is about 200 msec on a single SPARC-10 platform for lexicon size of 10. A top choice performance of 96% is achieved on a database of postal words captured at 212 dpi.
This paper discusses sampling intervals of two-dimensional Gabor features in the two-dimensional pattern, orientation angle, and logarithmic frequency domains. The discussion on the feature stabilities for basic image...
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This paper discusses sampling intervals of two-dimensional Gabor features in the two-dimensional pattern, orientation angle, and logarithmic frequency domains. The discussion on the feature stabilities for basic image transformations clarifies the stable range for translation, rotation and scaling. These stable ranges directly lead to sampling intervals for the individual feature domains. Multi-resolution features are constructed in terms of the combination of elements optimally sampled in the feature domains. The features of the optimal sampling intervals are examined in printed Japanese character recognition. The optimal sampling intervals maximize recognition rates at the same time as keeping computational cost low.
One difficulty with many pixel-wise thinning algorithms is that they produce unacceptable results at junction points, or in the presence of contour noise. The authors present a novel approach to detecting ambiguous re...
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One difficulty with many pixel-wise thinning algorithms is that they produce unacceptable results at junction points, or in the presence of contour noise. The authors present a novel approach to detecting ambiguous regions in a thinned image. The method uses the reconstructability properties of appropriate thinning algorithms to reverse the thinning process and automatically detect those pixels which may have resulted from more then one stroke in the image. The ambiguous regions are then interpreted and reconstructed using domain specific or derived contextual information. The approach has the advantage of using local methods to rapidly identify strokes (or regions) which have been thinned correctly and allowing more detailed analysis based on non-local methods in the remaining regions.
In a binary image contours may be seen as the discriminating curve between objects and background. Contours of connected components are always a Jordan curve. One symbol (e.g., a character) may consist of more than on...
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In a binary image contours may be seen as the discriminating curve between objects and background. Contours of connected components are always a Jordan curve. One symbol (e.g., a character) may consist of more than one such curve. Processing these curves is a one-dimensional task. Almost all common processing steps can be designed to work on contours rather than on the two-dimensional image. Moreover, contour processing gives new insight to well know problems and enables new processing steps or produces more information about the relations between connected components or objects of the image. The authors present preprocessing operations which work directly on the level of contours. Compared to the corresponding iconic operations, algorithms working on the contour level are mostly more efficient. Based on the contours of the connected components methods for filtering and slant normalization are described.
This paper discusses a technique for locating the courtesy amount block on bank checks. In the analysis and recognition process, connected components in the image are identified first. Then, strings are constructed on...
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This paper discusses a technique for locating the courtesy amount block on bank checks. In the analysis and recognition process, connected components in the image are identified first. Then, strings are constructed on the basis of proximity and horizontal alignment of characters. Next, a set of rules and heuristics are applied to these strings to choose the correct one. The chosen string is only accepted if it passes a verification test, which includes an attempt to recognize the currency sign. A deterministic finite automaton system is then used for segmenting the handprinted courtesy amount. Finally, the separated components are passed on to a neural network based recognition system.
Character recognition and texture segmentation are performed by a filter based on morphological opening. The filter is characterized by two shape patterns, one of them being larger than the other. If it is applied to ...
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ISBN:
(纸本)0818671289
Character recognition and texture segmentation are performed by a filter based on morphological opening. The filter is characterized by two shape patterns, one of them being larger than the other. If it is applied to an image, the output image will keep only the image objects which are smaller than the large shape pattern but larger that the small one. Thus, the filter has shape band-pass characteristics. It is used for character recognition and texture segmentation. Experimental results show the good performance of the filter for these purposes.
A symbolic/neural approach to recognize unconstrained handwritten cursive amounts in bank cheques is proposed. Features like ascenders and descenders are extracted from the binary image of the amount. Depending on the...
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A symbolic/neural approach to recognize unconstrained handwritten cursive amounts in bank cheques is proposed. Features like ascenders and descenders are extracted from the binary image of the amount. Depending on the features extracted, some words are recognized entirely symbolically, some words entirely neurally, and the remaining both symbolically and neurally. Results of preliminary experiments are provided.
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