We present a new off-line word recognition system that is able to recognise unconstrained handwritten words from their grey-scale images, and is based on structural and relational information in the handwritten word. ...
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Proposes a simple and powerful approach for texture classification using the eigenfeatures of local covariance measures. A texton encoder produces a texture code which is invariant to local and global textural rotatio...
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Laser radar has been used in scene distance measure since 80' s. Because of its initiative character , we can obtain images without the influence of light conditions;no matter day and night , the results are the s...
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Proposes a simple and powerful approach for texture classification using the eigenfeatures of local covariance measures. A texton encoder produces a texture code which is invariant to local and global textural rotatio...
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Proposes a simple and powerful approach for texture classification using the eigenfeatures of local covariance measures. A texton encoder produces a texture code which is invariant to local and global textural rotations. The proposed method uses six statistical features obtained from two scales of this invariant encoder to result in indices for roughness, anisotropy, and other higher-order textural features. Classification results for synthetic and natural textures are presented. The authors also discuss the effect of window sizes used at local and global scales on the performance of the classifier.< >
We present a new off-line word recognition system that is able to recognise unconstrained handwritten words from their grey-scale images, and is based on structural and relational information in the handwritten word. ...
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We present a new off-line word recognition system that is able to recognise unconstrained handwritten words from their grey-scale images, and is based on structural and relational information in the handwritten word. We use Gabor filters to extract features from the words, and then use an evidence-based approach for word classification. A solution to the Gabor filter parameter estimation problem is given, enabling the Gabor filter to be automatically tuned to the word image properties. Our experiments show that the proposed method achieves reasonably high recognition rates compared to standard classification methods.< >
Image processing techniques have already been widely used in various medical applications for decades. With the development of computer and image processing techniques, more and more medical diagnostic systems have be...
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With the development of computer and image processing techniques, the image processing techniques have been widely used in many of the medical applications for decades. Many of these applications are in the fields of ...
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As range images, obtained by active LAser raDAR (LADAR), contain the 3D information necessary for 3D environment understanding, great attention has been attracted, in the field of computervision, to the processing of...
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An optimal learning scheme is proposed for a class of bidirectional associative memories (BAMs). This scheme, based on the perceptron learning algorithm, is motivated by the inadequacies/incompleteness of the weighted...
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An optimal learning scheme is proposed for a class of bidirectional associative memories (BAMs). This scheme, based on the perceptron learning algorithm, is motivated by the inadequacies/incompleteness of the weighted learning by global optimization, as derived by Wang et al. (1993). It is shown that the new scheme has superior properties: (1) Convergence to the correct solution, when it exists; and (2) A larger basin of attraction for the given set of patterns.
In this paper, we present a recognition method which is developed for recognizing shape distorted and partially overlapped flat objects. Several features which are invariant or insensitive to the shape distortions cau...
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In this paper, we present a recognition method which is developed for recognizing shape distorted and partially overlapped flat objects. Several features which are invariant or insensitive to the shape distortions caused by position, scalling and 3-D rotation are proposed. A hierarchical description and Batching technique of the features make the recognition method powerful. The results of a series of experiments demonstrated that the method can be used in robot vision system.
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