Fusion of Matching Algorithms for Human Identification Using Dental X-Ray Radiographs

2012 Annual IEEE India Conference (INDICON)

Vijayakumari

2012

Forensic dentistry involves the identification of people based on their dental records, mainly available as radiographic images. Human identification is done by matching the given post-mortem radiographs with the antemortem images. In this paper, a computer-aided dental identification system for matching dental records is presented. The tooth contour is used as a feature for matching here. The proposed algorithm consists of five stages. As an initial step, the image is preprocessed. Then it is isolated as individual tooth by radiograph segmentation. Shape extraction is made using connected component labeling. Finding similarity metric is the next step. Various distance measures are also applied to find better matching. Finally candidate matching is done by obtaining the percentage of match between the original and extracted shape using both the similarity and distance measures. Experimental results show that the finer matching distance is observed by the distance metric rather than similarity measures. The experimental results are obtained on a database of 100 dental images which includes both periapical and bitewing. The results show that a high hit rate is observed for the Euclidean distance measure and which is comparable with the other methods.

Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Human forensic identification with dental radiographs using similarity and distance metrics

Pushparaj

2012 Annual IEEE India Conference (INDICON)

Vijayakumari

2012

“…The usage of photograph for human identification in addition with radiographs is detailed in [8]. In [9], the three different possible matching algorithms are dealt. Teeth numbering is one of the main goals in dental identification system, which is explained by Nomir et al, for bitewing radiographs [10].…”

Section: Related Workmentioning

confidence: 99%

“…It accomplishes two steps. Template matching is performed at first and subsequently tooth number assigning is taken part as per universal numbering system In general, two standard teeth patterns were available for bitewing images [9]. The teeth pattern for radiographic images is shown in table I.…”

Section: Teeth Numberingmentioning

confidence: 99%

An effective numbering and classification system for dental panoramic radiographs

Pushparaj

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

Banumathi

et al. 2013

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.

“…Said et al [4] offered a mathematical morphology approach, which used a series of morphology filtering operations to improve the segmentation, and then analyzed the connected components to obtain the desired region of interest. Paper [5] explains three different fusion approaches for the matching algorithms to get better matching between ante-and post-mortem images. Human identification using the shape and appearance of the tooth is explained in [6].…”

Section: Introductionmentioning

confidence: 99%

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

Pushparaj¹,

Vijayakumari³

2012

J Digit Imaging

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.