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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.


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Journal ArticleDOI
TL;DR: A character image restoration method is proposed for unconstrained handwritten Chinese character recognition that extends some state-of-the-art classifiers based on the estimated features and shows that the extended classifiers outperform the original state of the art classifiers.
Abstract: Despite the success of methods on constrained handwriting databases, recognition of unconstrained handwritten Chinese characters remains a big challenge. One difficulty for recognizing unconstrained handwritting is that some connected strokes are involved or some strokes are omitted. In this paper, a character image restoration method is proposed for unconstrained handwritten Chinese character recognition. In this method, the observed character image is modeled as the combination of the ideal character image with two types of noise images: the omitted stroke noise image and the added stroke noise image. To preserve the original gradient features, restoration is done on the gradient features. The estimated features are then used to discriminate similar characters. To show the effectiveness of the proposed method, we extend some state-of-the-art classifiers based on the estimated features. Experimental results show that the extended classifiers outperform the original state-of-the-art classifiers. This demonstrates that the estimated features are useful for further improving the recognition rate.

11 citations

01 Jan 2013
TL;DR: A system of English handwriting recognition based on 40-point feature extraction of the character based on multilayer feed forward neural network that will be suitable for converting handwritten documents into structural text form and recognizing handwritten names.
Abstract: We present in this paper a system of English handwriting recognition based on 40-point feature extraction of the character. Basically an off-line handwritten alphabetical character recognition system using multilayer feed forward neural network has been described in our work. Firstly a new method, called, 40-point feature extraction is introduced for extracting the features of the handwritten alphabets. Secondly, we use the data to train the artificial neural network. In the end, we test the artificial neural network and conclude that this method has a good performance at handwritten character recognition. This system will be suitable for converting handwritten documents into structural text form and recognizing handwritten names.

11 citations

Proceedings ArticleDOI
12 Oct 1997
TL;DR: An original method for the recognition of online handwritten Chinese characters using an improved syntactic pattern recognition using Kohonen's self-organizing feature map for feature extraction, to get optimal sets of prototypical waveforms of peaks from sample data automatically.
Abstract: We propose an original method for the recognition of online handwritten Chinese characters using an improved syntactic pattern recognition. Syntactic pattern recognition is a method that converts a pattern into a string of symbols using a finite set of features and then analyzes them structurally using grammars. It is effective for such patterns as structurally constructed Chinese characters. We use Kohonen's self-organizing feature map for feature extraction, to get optimal sets of prototypical waveforms of peaks from sample data automatically. The strings of symbols are converted into matrices which express features of the successors, and are analyzed by simple calculations between matrices. Moreover in order to symbolize and analyze efficiently and accurately in a large scale, we employ a hierarchical approach for the proposed method. Using free writing characters, we obtained a 99.49% recognition rate for training patterns and 94.34% for test patterns.

11 citations

Dissertation
01 Oct 2010
TL;DR: An attempt is made to evaluate the phytochemical properties of polymethine, which has potential in finding its applications in medicine and in the food industry.
Abstract: ......................................................................................................................................... I ACKNOWLEDGMENT .................................................................................................................... III PUBLICATIONS ............................................................................................................................... IV TABLE OF CONTENTS ................................................................................................................... VI LIST OF FIGURES ........................................................................................................................... IX LIST OF TABLES ............................................................................................................................... X LIST OF ABBREVIATIONS ............................................................................................................ XI CHAPTER ONE .................................................................................................................................. 1

11 citations

Proceedings ArticleDOI
01 Dec 2015
TL;DR: A word-based off-line Arabic handwritten recognition system based on discrete cosine transform features and SVM classifier enhanced using a reject option based on the number of sub-words in the input word image calculated using a novel segmentation algorithm.
Abstract: Arabic handwritten recognition is a challenging task due to high variability of Arabic script and its intrinsic characteristics such as cursiveness, ligatures and diacritics. This paper presents a word-based off-line Arabic handwritten recognition system based on discrete cosine transform features and SVM classifier enhanced using a reject option. The latter is based on the number of sub-words in the input word image calculated using a novel segmentation algorithm. To evaluate our proposed system, we used the IFN/ENIT database of Arabic handwritten words and the results has shown the effectiveness of our approach in enhancing the recognition performance.

11 citations


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