• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2011.10a
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• pp.287-290
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• 2011

The synchronization feature on the smartphone by default (default) value is set. Smartphone synchronization has been set is stored that smartphone data is automatically backed up is stored When connected to a PC with a smartphone dedicated cable. The backup data is a common technique to analyze the content to be difficult to apply forensic techniques can find out information on criminal suspects. In this paper, the backup data is synchronized to the smartphone through forensic analysis is the study of forensic evidence. In a lab environment to send personal financial information on smartphone, smartphone is assumed that the experiment is compromised. Smartphone's backup data by using the forensic tools in crime associated with personal financial information and analyze data. And, to be adopted by the court will study the evidence leveraging forensic technology. Through this paper as a basis for smartphone forensic analysis will be utilized.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.10
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• pp.2231-2238
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• 2011

In this paper, the extract method of eye and eye-line from picture of a person is proposed. Most of existing papers are to extract the position of eyeball but in this paper, by extracting not only the position of eyeball but also eye-line, it can be applied to the face application program variously. The experimental data of the input picture is a full face photograph taken by smart phone, basically the picture is limited to the face of one person and back ground can be taken from every where and no restriction of race. The proposed method is to extract face candidated area by using Harr Classifier and set up the candidate area of eye position from face candidate area. To extract high value from eye candidate area using dilate operation, and proposed the method to classify eye and eyelash by local thresholding of the picture. After that, using thresholding image from eyemapC that Hsu's suggested, and separated the area with eye and without eye. Finally extract the contour of eye and detect eye-line using optimum ellipse estimation.