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Biometric personal identification based on handwriting
In this paper, we describe a new method to identify the writer of Chinese handwritten documents. There are many methods for signature verification or writer identification, but most of them require segmentation or connected component analysis. They are content dependent identification methods, as si...
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| container_end_page | 800 vol.2 |
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| creator | Yong Zhu Tieniu Tan Yunhong Wang |
| description | In this paper, we describe a new method to identify the writer of Chinese handwritten documents. There are many methods for signature verification or writer identification, but most of them require segmentation or connected component analysis. They are content dependent identification methods, as signature verification requires the writer to write the same text (e.g. his name). In our new method, we take the handwriting as an image containing some special texture, and writer identification is regarded as texture identification. This is a content independent method. We apply the well-established 2D Gabor filtering technique to extract features of such textures and a weighted Euclidean distance classifier to fulfil the identification task. Experiments are made using Chinese handwritings from 17 different people and very promising results were achieved. |
| doi_str_mv | 10.1109/ICPR.2000.906196 |
| format | conference_proceeding |
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There are many methods for signature verification or writer identification, but most of them require segmentation or connected component analysis. They are content dependent identification methods, as signature verification requires the writer to write the same text (e.g. his name). In our new method, we take the handwriting as an image containing some special texture, and writer identification is regarded as texture identification. This is a content independent method. We apply the well-established 2D Gabor filtering technique to extract features of such textures and a weighted Euclidean distance classifier to fulfil the identification task. 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ICPR-2000</title><addtitle>ICPR</addtitle><description>In this paper, we describe a new method to identify the writer of Chinese handwritten documents. There are many methods for signature verification or writer identification, but most of them require segmentation or connected component analysis. They are content dependent identification methods, as signature verification requires the writer to write the same text (e.g. his name). In our new method, we take the handwriting as an image containing some special texture, and writer identification is regarded as texture identification. This is a content independent method. We apply the well-established 2D Gabor filtering technique to extract features of such textures and a weighted Euclidean distance classifier to fulfil the identification task. Experiments are made using Chinese handwritings from 17 different people and very promising results were achieved.</description><subject>Automation</subject><subject>Biometrics</subject><subject>Feature extraction</subject><subject>Filtering</subject><subject>Flowcharts</subject><subject>Gabor filters</subject><subject>Handwriting recognition</subject><subject>Image segmentation</subject><subject>Laboratories</subject><subject>Pattern recognition</subject><issn>1051-4651</issn><issn>2831-7475</issn><isbn>9780769507507</isbn><isbn>0769507506</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2000</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><recordid>eNotj1tLw0AQhRcvYKx9F5_yBxJnkt3J7KMGL4VCi-hz2exOdKVNShIQ_72BCgfO93T4jlK3CDki2PtVvX3LCwDILRBaOlNJwSVmla7MuVraiqEia6Cac6ESBIOZJoNX6nocvwEKKA0nih5jf5BpiD49yjD2ndunMUg3xTZ6N8W-Sxs3Skhn-HJd-BniFLvPG3XZuv0oy_9eqI_np_f6NVtvXlb1wzrzWOopM5ZC48A1YEzhWTRaxEAajQF2QQdvXSCyxNDybCwBmSUU5BmRNZcLdXfajSKyOw7x4Ibf3elx-Qc6ukcP</recordid><startdate>2000</startdate><enddate>2000</enddate><creator>Yong Zhu</creator><creator>Tieniu Tan</creator><creator>Yunhong Wang</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>2000</creationdate><title>Biometric personal identification based on handwriting</title><author>Yong Zhu ; Tieniu Tan ; Yunhong Wang</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c134t-596dba0ab0552c8e41911d6415508ad4dc9ad669680f8780ed188ed26c8118483</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2000</creationdate><topic>Automation</topic><topic>Biometrics</topic><topic>Feature extraction</topic><topic>Filtering</topic><topic>Flowcharts</topic><topic>Gabor filters</topic><topic>Handwriting recognition</topic><topic>Image segmentation</topic><topic>Laboratories</topic><topic>Pattern recognition</topic><toplevel>online_resources</toplevel><creatorcontrib>Yong Zhu</creatorcontrib><creatorcontrib>Tieniu Tan</creatorcontrib><creatorcontrib>Yunhong Wang</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Electronic Library (IEL)</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Yong Zhu</au><au>Tieniu Tan</au><au>Yunhong Wang</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Biometric personal identification based on handwriting</atitle><btitle>Proceedings 15th International Conference on Pattern Recognition. ICPR-2000</btitle><stitle>ICPR</stitle><date>2000</date><risdate>2000</risdate><volume>2</volume><spage>797</spage><epage>800 vol.2</epage><pages>797-800 vol.2</pages><issn>1051-4651</issn><eissn>2831-7475</eissn><isbn>9780769507507</isbn><isbn>0769507506</isbn><abstract>In this paper, we describe a new method to identify the writer of Chinese handwritten documents. There are many methods for signature verification or writer identification, but most of them require segmentation or connected component analysis. They are content dependent identification methods, as signature verification requires the writer to write the same text (e.g. his name). In our new method, we take the handwriting as an image containing some special texture, and writer identification is regarded as texture identification. This is a content independent method. We apply the well-established 2D Gabor filtering technique to extract features of such textures and a weighted Euclidean distance classifier to fulfil the identification task. Experiments are made using Chinese handwritings from 17 different people and very promising results were achieved.</abstract><pub>IEEE</pub><doi>10.1109/ICPR.2000.906196</doi></addata></record> |
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| identifier | ISSN: 1051-4651 |
| ispartof | Proceedings 15th International Conference on Pattern Recognition. ICPR-2000, 2000, Vol.2, p.797-800 vol.2 |
| issn | 1051-4651 2831-7475 |
| language | eng |
| recordid | cdi_ieee_primary_906196 |
| source | IEEE Electronic Library (IEL) Conference Proceedings |
| subjects | Automation Biometrics Feature extraction Filtering Flowcharts Gabor filters Handwriting recognition Image segmentation Laboratories Pattern recognition |
| title | Biometric personal identification based on handwriting |
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