Performance Analysis of Various Techniques Applied in Human Identification Using Dental X-Rays

Banumathi, A.; Vijayakumari, B.; Geetha, A.; Shanmugavadivu, N.; Raju, S. Sree Hari

doi:10.1007/s10916-007-9057-0

Cited by 17 publications

(15 citation statements)

References 5 publications

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“…The Mahalanobis distance is noted for each case. Figure 15a-c are the results of semiautomatic contour extraction method which was shown in our previous work [3]. For evaluation purpose, Mahalanobis distance is obtained for both these outputs by matching it with the original image.…”

Section: Resultsmentioning

confidence: 98%

“…The shortcomings in their approach are if the image is too blurred, their algorithm is not applicable and slight angle deviation in the ante-mortem and postmortem images may not be handled with this approach. Morphological corner detection algorithm and Gaussian mask are used to extract the shape of tooth contour in [3]. But Gaussian method does not show satisfying results for all the images.…”

Section: Introductionmentioning

confidence: 99%

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An Effective Dental Shape Extraction Algorithm Using Contour Information and Matching by Mahalanobis Distance

Pushparaj¹,

Ulaganathan²,

Vijayakumari³

2012

J Digit Imaging

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Human identification using dental radiographs is important in biometrics. Dental radiographs are mainly helpful for individual and mass disaster identification. In the 2004 tsunami, dental records were proven as the primary identifier of victims. So, this work aims to produce an automatic person identification system with shape extraction and matching techniques. For shape extraction, the available information is edge details, structural content, salient points derived from contours and surfaces, and statistical moments. Out of all these features, tooth contour information is a suitable choice here because it can provide better matching. This proposed method consists of four stages. The first step is preprocessing. The second one involves integral intensity projection for segmenting upper jaw, lower jaw, and individual tooth separately. Using connected component labeling, shape extraction was done in the third stage. The outputs obtained from the previous stage for some misaligned images are not satisfactory. So, it is improved by fast connected component labeling. The fourth stage is calculating Mahalanobis distance measure as a means of matching dental records. The matching distance observed for this method is comparatively better when it is compared with the semi-automatic contour extraction method which is our earlier work.

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Section: Resultsmentioning

confidence: 98%

Section: Introductionmentioning

confidence: 99%

An Effective Dental Shape Extraction Algorithm Using Contour Information and Matching by Mahalanobis Distance

Pushparaj¹,

Ulaganathan²,

Vijayakumari³

2012

J Digit Imaging

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“…Some studies have applied automated methods to increase the identification efficiency and accuracy. Methods work with algorithms that recognize contour patterns and dental structure shapes [18][19] .…”

Section: Resultsmentioning

confidence: 99%

Potential contribution of periapical radiographic film image processing for forensic identification

Emiliano

Marinho

Oliveira

2016

RGO, Rev. Gaúch. Odontol.

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Periapical X-rays are the most common complementary tests in the dental clinic. The indication of image tests in forensic identification RESUMOAs radiografias periapicais são os exames complementares mais frequentes na clínica odontológica. A indicação de exames de imagens na identificação forense depende da qualidade das radiografias produzidas. A edição digital de radiografias convencionais pode melhorar a qualidade de imagem. O presente trabalho consiste em relatar a potencial contribuição do processamento digital de filmes radiográficos através de relato de caso de identificação positiva por radiografias periapicais editadas digitalmente. Os resultados dos exames antropológicos e dos arcos dentários da vítima correspondiam às informações cedidas pelos familiares sobre a pessoa desaparecida. As radiografias periapicais antemortem e postmortem foram digitalizadas em scanner fotográfico (HP Development Company, HP ScanJet G4050 Photo, Estados Unidos) e as imagens processadas no programa de edição Corel PaintShop Pro X4 (Corel® Corporation, v14, Canadá). A comparação das imagens digitais das radiografias periapicais antemortem e postmortem permitiu determinar 8 pontos concordantes no contorno e delimitação do seio maxilar e das estruturas dentária e periodontal do elemento 17. A identificação do indivíduo foi possível mediante a edição digital das radiografias em programa de computador. A edição da permitiu ajustar imagens de brilho, contraste e nitidez e cores de temperatura e saturação das imagens das estruturas dento-maxilares. Esse recurso tecnológico contribuiu de forma efetiva para a identificação positiva realizada pela Odontologia Legal.Termos de indexação: Identificação forense. Imagem digital. Radiografias.

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“…The related work on affine transform based matching is detailed in [3]. Banumathi et al, used morphological contour and Gaussian filtering methods for dental shape extraction as given in [4]. Connected and fast connected component algorithms are utilized for dental shape extraction [5].…”

Section: Related Workmentioning

confidence: 99%

An effective numbering and classification system for dental panoramic radiographs

Pushparaj

Ulaganathan²,

Banumathi

et al. 2013

2013 Fourth International Conference on Computing, Communications and Networking Technologies (ICCCNT)

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In the current scenario, identifying a person in mass disasters is a challenging problem if adequate biometric information is not available. It can be handled by using dental radiographs as a suitable biometric means in such a circumstance. Forensic Odontology is a branch under biometrics which uses dental radiographs for human identification. In this paper an attempt is made to develop an algorithm for teeth numbering and classification, which is a major section in Automated Dental Identification system. Individual identification using dental panoramic images is an issue addressed in the literature. Hence, this work makes use of panoramic images for emerging this algorithm. The dental radiographs are initially preprocessed and each tooth is isolated for further processing. This image is subjected to Support Vector Machine classifier to segregate the tooth as Molar or Premolar. Then template matching algorithm followed by Universal numbering system is used to number the teeth. Experimental results show that this algorithm has numbering accuracy of 93.3% for Molar and 92% for premolar.

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Performance Analysis of Various Techniques Applied in Human Identification Using Dental X-Rays

Cited by 17 publications

References 5 publications

An Effective Dental Shape Extraction Algorithm Using Contour Information and Matching by Mahalanobis Distance

An Effective Dental Shape Extraction Algorithm Using Contour Information and Matching by Mahalanobis Distance

Potential contribution of periapical radiographic film image processing for forensic identification

An effective numbering and classification system for dental panoramic radiographs

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