Journal ArticleDOI
Invariant planar shape recognition using dynamic alignment
Lalit Gupta,Mandyam D. Srinath +1 more
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TLDR
Close planar shapes are modelled by an ordered sequence that represents the Euclidean distance between the centroid and all contour pixels of the shape by developing a dynamic alignment process to find the best correspondence between the sequences.About:
This article is published in Pattern Recognition.The article was published on 1988-05-01. It has received 36 citations till now. The article focuses on the topics: Euclidean distance & Centroid.read more
Citations
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Journal ArticleDOI
Improved moment invariants for shape discrimination
TL;DR: Improved moment invariants computed using the shape boundary only are proposed, which tremendously reduces computations and are mathematically proved to be invariant to scaling, translation, and rotation.
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Nonlinear alignment and averaging for estimating the evoked potential
TL;DR: A method which incorporates nonlinear alignment of the EPs into the averaging operation is developed, which addresses the problems associated with averaging brain responses evoked through a repetitive application of an external stimulus.
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A neural network approach to robust shape classification
TL;DR: A three layer perception using backpropagation is initially trained with contour sequences of noisefree reference shapes and the network is then gradually retrained with increasingly noisy data to improve the robustness of the classifier.
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Binary shape recognition using the morphological skeleton transform
TL;DR: A skeleton matching algorithm is presented that efficiently characterizes the similarity between two skeletons as a distance measure that resembles the well known from speech processing elastic matching technique.
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Robust partial shape classification using invariant breakpoints and dynamic alignment
Lalit Gupta,K. Malakapalli +1 more
TL;DR: An iterative algorithm derived from the colinearity principle is developed to locate invariant breakpoints on a shape contour and it is demonstrated that reasonable classification is obtained for noisy shapes with 0 to 30% occlusion.
References
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Journal ArticleDOI
Dynamic programming algorithm optimization for spoken word recognition
TL;DR: This paper reports on an optimum dynamic progxamming (DP) based time-normalization algorithm for spoken word recognition, in which the warping function slope is restricted so as to improve discrimination between words in different categories.
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Performance tradeoffs in dynamic time warping algorithms for isolated word recognition
TL;DR: The results suggest a new approach to dynamic time warping for isolated words in which both the reference and test patterns are linearly warped to a fixed length, and then a simplified dynamic time Warping algorithm is used to handle the nonlinear component of the time alignment.
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Improvements in isolated word recognition
M. Kuhn,H. Tomaschewski +1 more
TL;DR: Possibility for improving the recognition accuracy are investigated for a given feature extraction, which is based on a short term spectrum analysis by means of band-pass filtering and a method based on spectral change is investigated, alone and in combination with dynamic programming.