Results 1 - 10 of 35

Learning Discriminant Tangent Models for Handwritten Character Recognition

by Holger Schwenk, Maurice Milgram - In ICANN*96 , 1995
"... : Transformation invariance is known to be fundamental for excellent performances in pattern recognition. One of the most successful approach is tangent distance, originally proposed for a nearest-neighbor algorithm (Simard, LeCun and Denker, 1993). The resulting classifier, however, has a very high ..."
Abstract - Cited by 13 (5 self) - Add to MetaCart
. However, we often have high-level knowledge about the learning problem. In optical character recognition (...

Generalized Hough Transform for Arabic Printed Optical Character Recognition

by Sofien Touj, Najoua Ben Amara, Hamid Amiri , 2004
"... Abstract: The Hough Transform (HT) is a technique commonly used in image processing. It is known for its capacity to detect objects in a given image. In the present paper, we propose to explore the properties of the HT and the use of the Generalized HT (GHT) in Arabic Optical Character Recognition ( ..."
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Abstract: The Hough Transform (HT) is a technique commonly used in image processing. It is known for its capacity to detect objects in a given image. In the present paper, we propose to explore the properties of the HT and the use of the Generalized HT (GHT) in Arabic Optical Character Recognition

Optical Chinese Character Recognition using Probabilistic Neural Networks

by Richard Romero David, David Touretzky, Robert Thibadeau - Pattern Recognition , 1997
"... Building on previous work in Chinese character recognition, we describe an advanced system of classification using probabilistic neural networks. Training of the classifier starts with the use of distortion modeled characters from four fonts. Statistical measures are taken on a set of features compu ..."
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Building on previous work in Chinese character recognition, we describe an advanced system of classification using probabilistic neural networks. Training of the classifier starts with the use of distortion modeled characters from four fonts. Statistical measures are taken on a set of features

nerative Models for andwritten Digit Recognition

by Michael Revow, Christopher K. I. Williams, Geoffrey E. Hinton
"... Abstract-We describe a method of recognizing handwritten digits by fitting generative models that are built from deformable B-splines with Gaussian "ink generators " spaced along the length of the spline. The splines are adjusted using a novel elastic matching procedure based on the Expect ..."
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disadvantage of the method is it requires much more computation than more standard OCR techniques. Index Terms-Deformable model, elastic net, optical character recognition, generative model, probabilistic model, mixture model 1

Face Recognition by Applying Wavelet Subband Representation and Kernel Associative Memory

by Bai-ling Zhang, Haihong Zhang, Shuzhi Sam Ge, Senior Member - IEEE Transactions on neural networks , 2004
"... Abstract—In this paper, we propose an efficient face recognition scheme which has two features: 1) representation of face images by two-dimensional (2-D) wavelet subband coefficients and 2) recog-nition by a modular, personalised classification method based on kernel associative memory models. Compa ..."
Abstract - Cited by 37 (5 self) - Add to MetaCart
for face recognition is inspired by the same motivation as using autoencoders for optical character recognition (OCR), for which the advantages has been proven. By associative memory, all the prototypical faces of one particular person are used to reconstruct themselves and the reconstruction error for a

Word spotting: A new approach to indexing handwriting

by R. Manmatha, Chengfeng Han, E. M. Riseman - IN PROC. OF THE CONF. ON COMPUTER VISION AND PATTERN RECOGNITION , 1996
"... There are many historical manuscripts written in a single hand which it would be useful to index. Examples include the early Presidential papers at the Library of Congress and the collected works of W. B. DuBois at the library of the University of Massachusetts. The standard technique for indexing d ..."
Abstract - Cited by 70 (9 self) - Add to MetaCart
documents is to scan them in, convert them to machine readable form (ASCII) using Optical Character Recognition (OCR) and then index them using a text retrieval engine. However, OCR does not work well on handwriting. Here an alternative scheme is proposed for indexing such texts. Each page of the document

D.: Coherence of Off-Topic Responses for a Virtual Character

by Ron Artstein, Jacob Cannon, Sudeep G, Jillian Gerten, Joe Henderer, Anton Leuski, David Traum - In: 26th Army Science Conference , 2008
"... We demonstrate three classes of off-topic responses which allow a virtual question-answering character to handle cases where it does not understand the user’s input: ask for clarification, indicate misunderstanding, and move on with the conversation. While falling short of full dialogue management, ..."
Abstract - Cited by 1 (1 self) - Add to MetaCart
life-size character built for demos in mobile exhibits, who listens to human speech and responds with pre-recorded voice answers (Figure 1). SGT Star is based on technology similar to that used in previous efforts (Leuski et al., 2006; Leuski and Traum, 2008), which treats questionanswering

Segmentation free Bangla OCR using HMM: Training and Recognition

by Md. Abul Hasnat, S. M. Murtoza Habib, Mumit Khan - Proc. of 1st DCCA2007 , 2007
"... The wide area of the application of HMM is in Speech Recognition where each spoken word is considered as a single unit to be recognized from the trained word network. Using this concept some research has been done for character recognition. In this paper, we present the training and recognition mech ..."
Abstract - Cited by 2 (0 self) - Add to MetaCart
mechanism of a Hidden Markov Model (HMM) based multi font supported Optical Character Recognition (OCR) system for Bangla character. In our approach the central idea is separate HMM model for each segmented character or word. We emphasize on word level segmentation and like to consider the single character

A generative probabilistic ocr model for nlp applications

by Okan Kolak, William Byrne, Philip Resnik - In Proceedings of the Human Language Technology Conference (HLTNAACL
"... In this paper, we introduce a generative probabilistic optical character recognition (OCR) model that describes an end-to-end process in the noisy channel framework, progressing from generation of true text through its transformation into the noisy output of an OCR system. The model is designed for ..."
Abstract - Cited by 22 (1 self) - Add to MetaCart
In this paper, we introduce a generative probabilistic optical character recognition (OCR) model that describes an end-to-end process in the noisy channel framework, progressing from generation of true text through its transformation into the noisy output of an OCR system. The model is designed

2009 10th International Conference on Document Analysis and Recognition Learning on the Fly: Font-Free Approaches to Difficult OCR Problems

by Andrew Kae, Erik Learned-miller
"... Despite ubiquitous claims that optical character recognition (OCR) is a “solved problem, ” many categories of documents continue to break modern OCR software such as documents with moderate degradation or unusual fonts. Many approaches rely on pre-computed or stored character models, but these are v ..."
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Despite ubiquitous claims that optical character recognition (OCR) is a “solved problem, ” many categories of documents continue to break modern OCR software such as documents with moderate degradation or unusual fonts. Many approaches rely on pre-computed or stored character models
Results 1 - 10 of 35