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Intelligent word recognition

About: Intelligent word recognition is a research topic. Over the lifetime, 2480 publications have been published within this topic receiving 45813 citations.


Papers
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Proceedings ArticleDOI
23 Aug 2004
TL;DR: This paper constructed a system that can read characters to support a guide dog system with character recognition ability, and focuses exclusively on reading a room number.
Abstract: This paper introduces a guide dog system with character recognition ability. The main purpose of this system is to assist blind people. A guide dog helps a visually impaired person to act corresponding to the surrounding environment. However, it cannot do complex tasks such as reading words. We constructed a system that can read characters to support them. Usually, character recognition systems segment character from the general background by using some information. This time, our system focuses exclusively on reading a room number. Therefore, we used a method of character searching by template matching.

23 citations

Journal ArticleDOI
TL;DR: This paper describes two approaches for Amharic word recognition in unconstrained handwritten text using HMMs, the first approach builds word models from concatenated features of constituent characters and in the second method HMMs of constituentCharacters are concatenate to form word model.

23 citations

Proceedings ArticleDOI
30 Aug 1992
TL;DR: The authors present a universal shape characterization method applied to the domain of off-line handwritten characters and points out previous work in the area of 2D shape classification and handwriting recognition.
Abstract: Handwritten characters are forms. Thus they are accessible to form description methods. The authors present a universal shape characterization method applied to the domain of off-line handwritten characters. The test universe is restricted to the ten Arabic numerals but can be extended to any other characters. The authors point out previous work in the area of 2D shape classification and handwriting recognition. The theoretical concept of the authors' shape descriptor is introduced together with a recipe to apply it in the real case of discrete binary images. Results of classification experiments are presented. >

23 citations

Proceedings ArticleDOI
10 Sep 2001
TL;DR: An off-line system under development to process unconstrained handwritten dates on Brazilian bank cheques in an omni-writer context and shows improvements on previous work on isolated month word recognition using hidden Markov models (HMM).
Abstract: This paper describes an off-line system under development to process unconstrained handwritten dates on Brazilian bank cheques in an omni-writer context. We show here some improvements on our previous work on isolated month word recognition using hidden Markov models (HMM). After preprocessing, a word image is explicitly segmented into characters or pseudo-characters and represented by two feature sequences of equal length, which are combined using HMM. The word models are generated from the concatenation of appropriate character models. In addition to the small date database, we also make use of the legal amount database to increase the frequency of characters in the training and the validation sets. Although this study deals with a limited lexicon, the many similarities among the word classes can affect the performance of the recognition. Experiments show an increase in the average recognition rate from 84% to 91%. Finally, we present our perspectives of future work.

23 citations

Proceedings ArticleDOI
01 Oct 2016
TL;DR: This work proposes a method based on perceptual grouping for the recognition of compound music notes and has been tested using several handwritten music scores of the CVC-MUSCIMA database and compared with a commercial Optical Music Recognition software.
Abstract: The recognition of handwritten music scores still remains an open problem. The existing approaches can only deal with very simple handwritten scores mainly because of the variability in the handwriting style and the variability in the composition of groups of music notes (i.e. compound music notes). In this work we focus on this second problem and propose a method based on perceptual grouping for the recognition of compound music notes. Our method has been tested using several handwritten music scores of the CVC-MUSCIMA database and compared with a commercial Optical Music Recognition (OMR) software. Given that our method is learning-free, the obtained results are promising.

23 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
202314
202241
20201
20192
20189
201751