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標題: 牙齒X光片與牙齒治療之分類方法
Effective Classification Methods for Dental Radiographs and Dental Works
作者: 余俊德
Yu, Jyun-De
關鍵字: Dental Radiographs;牙齒X光片;Dental Works;牙齒治療;牙齒辨識
出版社: 資訊網路多媒體研究所
引用: [1]National Science and Technology Council(NTSC) Subcommittee on Biometrics, [2]International Biometric Group, [3]Phen-Lan Lin, Yan-Hao Lai, Po-Whei Huang,"An Effective Classification and Numbering System for Dental Bitewing Radiographs Using Teeth Region and Contour Information".Pattern Recognition, Vol. 4 , No. 43 , p.p.80 -92 [4]Diaa Eldin Nassar,Ayman Abaza,Xin Li,Hany Ammar,"Automatic Construction of Dental Charts for Postmortem Identification".IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY, VOL. 3, NO. 2,pp.234-246, JUNE 2008 [5]Jindan Zhou, Mohamed Abdel-Mottaleb,"Acontent-based system for human identification based on bitewing dental X-ray images",Pattern Recognition Letters, Vol. 38, pp. 2132-2142, 2005 [6]A.R. Webb, Statistical Pattern Recognition 2/e, John Wiley, 2002. [7] [8]C. Cortes, V. Vapnik, “Support Vector Network,” Mach. Learn., Vol. 20, pp. 273–297, 1995. [9]C.W. Hsu, C.J. Lin, “A Comparison on Methods for Multiclass Support Vector Machines,”.IEEE Trans.on Neural Network, Vol. 13, pp. 415-425, 2002 [10] [11] [12]Robert M.Haralick,K.Shanmugam,"Textural Features for Image Classfication",IEEE TRANSACTIONS ON SYSTEM,MAN AND CYBERNETICS VOL.SMC-3,NO.6,pp. 610-621,1973 [13]Leen-Kiat Soh,Costas Tsatsoulis,"Texture Analysis of SAR Sea Ice Imagery Using Gray Level Co-Occurrence Matrices",IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, VOL. 37, NO. 2,pp.780-795,MARCH 1999 [14]Michael Hofer, Aparecido Nilceu Marana,"Dental Biometrics:Human Identification Based on Dental Work Information",XX Brazilian Symposium on Computer Graphics and Image Processing [15]Phen-Lan Lin, Yan-Hao Lai, and Chun-Hung KuoLin, Phen-Lan (2011/1). Dental Identification based on Teeth and Dental Works Matching for Bitewing Radiographs. IEICE technical report. 日本:IEICE電子通信協會. [16]Rafael C. Gonzalez Richard E. Woods,Digital Image Processing 2/e,Princeton,2007 [17]Haralick, R. M., and L. G. Shapiro, Computer and Robot Vision, Vol. I, Addison-Wesley, 1992, pp. 158-205 [18]謬紹綱,數位影像處理-活用Matlab,全華科技圖書股份有限公司,民88 [19]Keinosuke Fukunaga,Introduction to statistical pattern recognition,2nd,New York:Academic,1990 [20]Po-Whei Huang,Cheng-Hsiung Lee,"Automatic Classification for Pathological Prostate. Images Based on Fractal Analysis".IEEE TRANSACTIONS ON MEDICAL IMAGING,VOL.28,NO. 7,pp.1037-1050,JULY 2009

In recent years, identity recognition technology is widely used in daily life, such as: iris, fingerprints, voice prints, facial recognition ... and so on. Varieties of biological characteristics are quickly applied in control, transaction security, law enforcement and other related fields. However, in the field of the legal profession, victims and biological characteristics of the behavior are often damaged cause of major accidents. Teeth are the hardest body tissue that can resist high temperatures and strong impact. It is very suitable as a basis for identification of the victims. Because of traditional method of dental identification required to identify on a large database manually, it is a time consuming and ineffective approach. An automated dental identification system is proposed to find the best fit people by comparing dental radiographs of victims (post-mortem) and the dental radiographs on database are recorded before his death (ante-mortem). In addition, all kinds of dental work, including filling, crowns, implants ... and so on have different characteristic, it can be used as a basis for supporting the identity recognition. Therefore, this paper proposed two methods, one is a hierarchical feature extraction method of classifying dental radiographs effectively. The other is a morphological feature extraction of classifying dental work effectively. An automated dental identification system can be achieved by these effective classifications.
其他識別: U0005-0908201114214900
Appears in Collections:資訊網路與多媒體研究所

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