NDLI: Tattoo skin cross - correlation neural network

Content Provider	IEEE Xplore Digital Library
Author	Duangphasuk, Pruegsa Kurutach, Werasak
Copyright Year	2014
Description	Author affiliation: Faculty of Information Science and Technology, Mahanakorn University of Technology, 140 Cheumsampan Road, Kratumrai, Nongjok, Bangkok, 10530 THAILAND (Duangphasuk, Pruegsa; Kurutach, Werasak)
Abstract	The soft biometric traits such as distinctive skin markings, tattoos based on its visual and demographic of tattoo are mostly used to identify a suspect or a victim in forensic sciences. Nevertheless, in many scenarios, police investigators type in the description of a suspect's tattoo based on text search, therefore these classifications make it difficult to recognize associated tattoo, for example, tattoos' criminal gangs. This paper proposed the tattoo skin recognition using cross - correlation neural network. This method has been designed into two steps: (1) the pre - processing part is keypoints feature extraction to distinguish tattoos from human skin and (2) the recognition process applies with cross-correlation neural network to classify and recognize the familiar tattoos. The tattoos database collected from prisoners in prison ministry, THAILAND. The experimental results indicated that the cross-correlation neural network outperforms the other methodologies by a wide margin. The overall accuracy obtained approximately 90.23% for tattoo skin recognition.
Starting Page	489
Ending Page	493
File Size	2267671
Page Count	5
File Format	PDF
ISBN	9781479944163
DOI	10.1109/ISCIT.2014.7011961
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-09-24
Publisher Place	South Korea
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Image color analysis Databases Forensics Neural networks Tattoos skin recognition feature extraction forensic science Feature extraction Skin Vectors machine learning cross-correlation neural network
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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