共查询到20条相似文献,搜索用时 15 毫秒
1.
Optical character recognition for cursive handwriting 总被引:5,自引:0,他引:5
Arica N. Yarman-Vural F.T. 《IEEE transactions on pattern analysis and machine intelligence》2002,24(6):801-813
A new analytic scheme, which uses a sequence of image segmentation and recognition algorithms, is proposed for the off-line cursive handwriting recognition problem. First, some global parameters, such as slant angle, baselines, stroke width and height, are estimated. Second, a segmentation method finds character segmentation paths by combining gray-scale and binary information. Third, a hidden Markov model (HMM) is employed for shape recognition to label and rank the character candidates. For this purpose, a string of codes is extracted from each segment to represent the character candidates. The estimation of feature space parameters is embedded in the HMM training stage together with the estimation of the HMM model parameters. Finally, information from a lexicon and from the HMM ranks is combined in a graph optimization problem for word-level recognition. This method corrects most of the errors produced by the segmentation and HMM ranking stages by maximizing an information measure in an efficient graph search algorithm. The experiments indicate higher recognition rates compared to the available methods reported in the literature 相似文献
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An off-line cursive handwriting recognition system 总被引:5,自引:0,他引:5
Senior A.W. Robinson A.J. 《IEEE transactions on pattern analysis and machine intelligence》1998,20(3):309-321
Describes a complete system for the recognition of off-line handwriting. Preprocessing techniques are described, including segmentation and normalization of word images to give invariance to scale, slant, slope and stroke thickness. Representation of the image is discussed and the skeleton and stroke features used are described. A recurrent neural network is used to estimate probabilities for the characters represented in the skeleton. The operation of the hidden Markov model that calculates the best word in the lexicon is also described. Issues of vocabulary choice, rejection, and out-of-vocabulary word recognition are discussed 相似文献
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A method of recognition of arabic cursive handwriting 总被引:1,自引:0,他引:1
Almuallim H Yamaguchi S 《IEEE transactions on pattern analysis and machine intelligence》1987,(5):715-722
In spite of the progress of machine recognition techniques of Latin, Kana, and Chinese characters over the two past decades, the machine recognition of Arabic characters has remained almost untouched. In this correspondence, a structural recognition method of Arabic cursively handwritten words is proposed. In this method, words are first segmented into strokes. Those strokes are then classified using their geometrical and topological properties. Finally, the relative position of the classified strokes are examined, and the strokes are combined in several steps into a string of characters that represents the recognized word. Experimental results on texts handwritten by two persons showed high recognition accuracy. 相似文献
4.
脱机自由手写英文单词的识别 总被引:1,自引:0,他引:1
介绍了一个基于隐马尔科夫模型的、采用模糊分割方式的脱机手写英文单词识别系统。该系统由图像预处理、特征提取、基于HMM的训练和识别四个模块组成。图像预处理中包括二值化、平滑去噪、倾斜校正和参考线提取。然后通过宽度不固定的滑动窗提取特征,前两组特征是整体形状和象素分布特征,另外又引入了Sobel梯度特征。HMM模型采用嵌入式的Baum-Welch算法训练,这种训练方式无需分割单词。最后用Viterbi算法识别。对字典中的每个单词,采用字母模型线性连接成单词模型。 相似文献
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Handwriting is considered as the output of a space variant imaging system equivalent to the writer. This system is described by the parameters of the synthesis of letters from a given model. A statistical analysis of the variations of this system on a set of successive pages leads to the extraction of writer features as well as the segmentation of the text into short-time stationarity domains to be related to “rhythms of writing”. 相似文献
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Katerin Romeo-Pakker Abderrahim Ameur Christian Olivier Yves Lecourtier 《Machine Vision and Applications》1995,8(4):232-240
In this paper, a structural method of recognising Arabic handwritten characters is proposed. The major problem in cursive text recognition is the segmentation into characters or into representative strokes. When we segment the cursive portions of words, we take into account the contextual properties of the Arabic grammar and the junction segments connecting the characters to each other along the writing line. The problem of overlapping characters is resolved with a contour-following algorithm associated with the labelling of the detected contours. In the recognition phase, the characters are gathered into ten families of candidate characters with similar shapes. Then a heterarchical analysis follows that checks the pattern via goal-directed feedback control. 相似文献
10.
Shimon Edelman Tamar Flash Shimon Ullman 《International Journal of Computer Vision》1990,5(3):303-331
We describe a new approach to the visual recognition of cursive handwriting. An effort is made to attain human-like performance by using a method based on pictorial alignment and on a model of the process of handwriting. The alignment approach permits recognition of character instances that appear embedded in connected strings. A system embodying this approach has been implemented and tested on five different word sets. The performance was stable both across words and across writers. The system exhibited a substantial ability to interpret cursive connected strings without recourse to lexical knowledge.SU is partially supported by NSF grant IRI-8900267. 相似文献
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Jungpil Shin Author Vitae 《Pattern recognition》2004,37(11):2101-2112
As a means to perform on-line recognition of cursive Korean characters, called hanguls, we describe a structural analysis type algorithm that searches globally for key points of segmentation on a character unit level and can cope with large variations in stroke shape and position. This “segmentation points search” is systematically performed by a two-level dynamic programming (DP) matching algorithm in conjunction with syntax control of hangul composition characteristics. Fine discrimination for phonemes and characters is effectively realized using mutual information among strokes. Experiments demonstrate computational feasibility and that the proposed approach provides high recognition and segmentation ability. 相似文献
12.
Jue Wang Chenyu Wu Ying-Qing Xu Heung-Yeung Shum 《International Journal on Document Analysis and Recognition》2005,7(4):219-227
This paper proposes a novel learning-based approach to synthesizing cursive handwriting of a user's personal handwriting style
by combining shape and physical models. In the training process, some sample paragraphs written by a user are collected and
these cursive handwriting samples are segmented into individual characters by using a two-level writer-independent segmentation
algorithm. Samples for each letter are then aligned and trained using shape models. In the synthesis process, a delta log-normal
model based conditional sampling algorithm is proposed to produce smooth and natural cursive handwriting of the user's style
from models.
Received: 26 April 2003, Accepted: 27 September 2004, Published online: 29 November 2004
Correspondence to: Jue Wang
Jue Wang and Chenyu Wu completed this work while interns at Microsoft Research Asia. 相似文献
13.
In this paper we describe a database that consists of handwritten English sentences. It is based on the Lancaster-Oslo/Bergen
(LOB) corpus. This corpus is a collection of texts that comprise about one million word instances. The database includes 1,066
forms produced by approximately 400 different writers. A total of 82,227 word instances out of a vocabulary of 10,841 words
occur in the collection. The database consists of full English sentences. It can serve as a basis for a variety of handwriting
recognition tasks. However, it is expected that the database would be particularly useful for recognition tasks where linguistic
knowledge beyond the lexicon level is used, because this knowledge can be automatically derived from the underlying corpus.
The database also includes a few image-processing procedures for extracting the handwritten text from the forms and the segmentation
of the text into lines and words.
Received September 28, 2001 / Revised October 10, 2001 相似文献
14.
M. Kobayashi S. Masaki O. Miyamoto Y. Nakagawa Y. Komiya T. Matsumoto 《International Journal on Document Analysis and Recognition》2001,3(3):181-191
A new algorithm RAV (reparameterized angle variations) is proposed which makes explicit use of trajectory information where the time evolution of the pen coordinates plays a crucial role. The algorithm is robust against stroke connections/abbreviations
as well as shape distortions, while maintaining reasonable robustness against stroke-order variations. Preliminary experiments
are reported on tests against the Kuchibue_d-96-02 database from the Tokyo University of Agriculture and Technology.
Received July 24, 2000 / Revised October 6, 2000 相似文献
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Ligature modeling for online cursive script recognition 总被引:2,自引:0,他引:2
Bong-Kee Sin Kim J.H. 《IEEE transactions on pattern analysis and machine intelligence》1997,19(6):623-633
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Off-line cursive script word recognition 总被引:2,自引:0,他引:2
Bozinovic R.M. Srihari S.N. 《IEEE transactions on pattern analysis and machine intelligence》1989,11(1):68-83
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In order to improve the performance of image segmentation, this paper presented a gray level jump segmentation algorithm, which defined the direction of the texture, simultaneously, calculated the width of ridge line, gave the distance characteristics between textures, and established the mathematical model of the texture border, accordingly presented a new texture segmentation algorithm and compared with other texture segmentation algorithms. The simulation results show that the segmentation algorithm has some advantages to texture segmentation, such as has higher segmentation precision, faster segmentation speed, stronger anti-noise capability, less lost information of target, and so on. The segmented regions hardly contain other texture regions and background region. Moreover, this paper extracted the characteristic points and characteristic parameters in various segmented regions for texture image to obtain the characteristic vector, compared the characteristic vector with the standard template vectors, and identified the type of target in a range of threshold value. Experimental results show that the proposed target recognition approach has higher recognition rate and faster recognition speed than the existing target recognition approaches. Advancements in image processing through the study of texture segmentation are not only applicable to image fields, but also are of important theoretical value to target recognition. These researches in this paper will play an important role in a theoretical reference and practical significance to the development of all target recognition departments based on image system such as the aerospace, public security, road traffic, and so on. 相似文献
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把二进制粒子群优化算法(BPSO)应用到人脸识别中.对人脸图像进行二维离散余弦变换(DCT),获得人脸图像的特征向量,应用BPSO算法对得到的特征向量进行特征选择,得到最具代表性的人脸特征.与遗传算法(GA)相比,在选择的特征较少的情况下,BPSO算法比遗传算法有更好的识别率.实验结果表明,BPSO算法应用到人脸识别中有较高的识别率,是一种非常有效的特征提取方法. 相似文献