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NaXi Pictographs Input Method and WEFT  [cached]
Hai Guo,Jing-ying Zhao
Journal of Computers , 2010, DOI: 10.4304/jcp.5.1.117-124
Abstract: NaXi Pictograph , which is the only hieroglyph in use is important for researching into the evolution of the character. In the past, processing NaXi Pictograph by hand, that is very inefficient. The NaXi Pictograph information processing modules is developed, such as pictograph Outline Font lib, the input method module, the embedded module and so on. A method of NaXi Pictographs Outline font extraction is proposed, which has been testified better in the Linux. As the specialty of NaXi Pictographs,two input mothods -- NaXi pictographs pinyin and graphic primitive input method are advanced, by evaluating ,which is found that the second is better than the first in precision. For display in web, The web embedding fonts technology of NaXi Pictographs is brought forward, and The web embedding fonts technology of NaXi pictographs makes Internet clients browse NaXi pictographs web without downloading NaXi pictographs font. The development of the NaXi Pictograph Information Processing System is significant to research into NaXi pictographs and apply it.
Rapid Feature Extraction for Optical Character Recognition  [PDF]
M. Zahid Hossain,M. Ashraful Amin,Hong Yan
Computer Science , 2012,
Abstract: Feature extraction is one of the fundamental problems of character recognition. The performance of character recognition system is depends on proper feature extraction and correct classifier selection. In this article, a rapid feature extraction method is proposed and named as Celled Projection (CP) that compute the projection of each section formed through partitioning an image. The recognition performance of the proposed method is compared with other widely used feature extraction methods that are intensively studied for many different scripts in literature. The experiments have been conducted using Bangla handwritten numerals along with three different well known classifiers which demonstrate comparable results including 94.12% recognition accuracy using celled projection.
A feature extraction technique based on character geometry for character recognition  [PDF]
Dinesh Dileep Gaurav,Renu Ramesh
Computer Science , 2012,
Abstract: This paper describes a geometry based technique for feature extraction applicable to segmentation-based word recognition systems. The proposed system extracts the geometric features of the character contour. This features are based on the basic line types that forms the character skeleton. The system gives a feature vector as its output. The feature vectors so generated from a training set, were then used to train a pattern recognition engine based on Neural Networks so that the system can be benchmarked.
TOPOGRAPHIC FEATURE EXTRACTION FOR BENGALI AND HINDI CHARACTER IMAGES
Soumen Bag,Gaurav Harit
Signal & Image Processing , 2011,
Abstract: Feature selection and extraction plays an important role in different classification based problems such as face recognition, signature verification, optical character recognition (OCR) etc. The performance of OCR highly depends on the proper selection and extraction of feature set. In this paper, we present novel features based on the topography of a character as visible from different viewing directions on a 2D plane. By topography of a character we mean the structural features of the strokes and their spatial relations. In this work we develop topographic features of strokes visible with respect to views from different directions (e.g. North, South, East, and West). We consider three types of topographic features: closed region, convexity of strokes, and straight line strokes. These features are represented as a shapebased graph which acts as an invariant feature set for discriminating very similar type characters efficiently. We have tested the proposed method on printed and handwritten Bengali and Hindi character images. Initial results demonstrate the efficacy of our approach.
Topographic Feature Extraction for Bengali and Hindi Character Images  [PDF]
Soumen Bag,Gaurav Harit
Computer Science , 2011, DOI: 10.5121/sipij.2011.2215
Abstract: Feature selection and extraction plays an important role in different classification based problems such as face recognition, signature verification, optical character recognition (OCR) etc. The performance of OCR highly depends on the proper selection and extraction of feature set. In this paper, we present novel features based on the topography of a character as visible from different viewing directions on a 2D plane. By topography of a character we mean the structural features of the strokes and their spatial relations. In this work we develop topographic features of strokes visible with respect to views from different directions (e.g. North, South, East, and West). We consider three types of topographic features: closed region, convexity of strokes, and straight line strokes. These features are represented as a shape-based graph which acts as an invariant feature set for discriminating very similar type characters efficiently. We have tested the proposed method on printed and handwritten Bengali and Hindi character images. Initial results demonstrate the efficacy of our approach.
Feature Dimension Reduction of NaXi Pictographs Characters Recognition based on LDA  [PDF]
Hai Guo,Jinghua Yin,Jingying Zhao
International Journal of Computer Science Issues , 2012,
Abstract: As a kind of pictographic character, Naxi pictographs character has received little academic attention. Proposing dimension reduction method of Naxi pictographs characters on the basis of LDA (Linear Discriminant Analysis), this paper thus makes an in-depth study of feature dimension reduction, an important issue in the recognition of Naxi pictographs characters. By constructing a recognition sample library involving four features of grid feature, permeability number feature, moment invariant feature, and directional element feature (DEF), 50% of data are selected from sample library as training set and testing set respectively. Two dimension reduction methods of LDA and FA (Factor Analysis) are applied to dimension reduction experiment of features of Naxi pictographs characters. The experiment result proves LDA method to be significantly superior to FA method, as LDA method could still maintain a 99% recognition precision when the dimension is reduced to 10% of the original dimension.
Combining Multiple Feature Extraction Techniques for Handwritten Devnagari Character Recognition  [PDF]
Sandhya Arora,Debotosh Bhattacharjee,Mita Nasipuri,Dipak Kumar Basu,Mahantapas Kundu
Computer Science , 2010,
Abstract: In this paper we present an OCR for Handwritten Devnagari Characters. Basic symbols are recognized by neural classifier. We have used four feature extraction techniques namely, intersection, shadow feature, chain code histogram and straight line fitting features. Shadow features are computed globally for character image while intersection features, chain code histogram features and line fitting features are computed by dividing the character image into different segments. Weighted majority voting technique is used for combining the classification decision obtained from four Multi Layer Perceptron(MLP) based classifier. On experimentation with a dataset of 4900 samples the overall recognition rate observed is 92.80% as we considered top five choices results. This method is compared with other recent methods for Handwritten Devnagari Character Recognition and it has been observed that this approach has better success rate than other methods.
A Survey of Feature Extraction and Classification Techniques Used In Character Recognition for Indian Scripts  [PDF]
Aditya Raj,Ranjeet Srivastva,Tushar Patnaik,Bhupendra Kumar
International Journal of Engineering and Advanced Technology , 2013,
Abstract: The Constitution of India has recognized 22 languages as official languages of India. Among these most of the recognition research work has been done for Devanagari, Gurumukhi, Telugu, and Bangla scripts etc. OCR system development for Indian script has many application areas like preserving manuscripts and ancient literatures written in different Indian scripts and making digital libraries for the documents. Feature extraction and classification are essential steps of character recognition process affecting the overall accuracy of the recognition system. This paper gives a detailed overview of different feature extraction and classification techniques for recognition process of different Indian scripts by the researchers over the past few decades
The Car Plate Chinese Character Feature Extraction Based on Wavelet
基于小波的车牌汉字特征提取

PAN Xiang,YE Xiu-zi,ZHANG San-yuan,
潘翔
,叶修梓,张三元

中国图象图形学报 , 2003,
Abstract: The car plate recognition system is an indispensable part of intelligent traffic system. In car plate recognition system, one of the most difficult problems is the feature and recognition of car plate Chinese character. The multiresolution property of wavelet is applied to extract car plate Chinese character feature extraction, and a method that directly extracts feature from gray scale image is proposed. The method firstly extracts two kinds of features: one is wavelet moments in different multiresolution, and the other is the zoning density of wavelet-decomposed image. Then, two kinds of features are combined and a feature selection algorithm based recognition rate is presented to choose better features. Finally, the selected features are as the input of BP neural network, which is adopted to recognize car plate Chinese character. As a result, the proposed method avoids the binary operation used in some traditional Chinese character feature extractions that will seriously destroy the Chinese character structure. Furthermore, the extracted features can describe the local and global property of the character. Compared with some other feature extraction methods, the proposed method can achieve better recognition performance.
Study of Several Handwritten Chinese Character Directional Feature Extraction Approaches
几种手写体汉字网格方向特征提取法的比较研究*

JIN Lian-wen,GAO Xue,
金连文
,高学

计算机应用研究 , 2004,
Abstract: Recently,it is found that the directional feature is considered suitable for Chinese character recognition,and directional feature has been widely used as one of the mainstream feature extraction approach.Directional decomposition algorithm and meshing method are two key factors in extraction of directional feature.This paper presents several directional features with different meshing methods for Handwritten Chinese Character Recognition (HCCR).Local elastic meshing technology is introduced in this paper,and it is found that local elastic meshing method is much better than global elastic meshing method.
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