Limitations of this demo version:
The only limitation of this demonstration version is that when adding images to the database, only 90% of the selected images will be considered. For using this software in commercial applications, a license for the full version must be obtained.
Current version: 0.62 Sept 22, 2015
Within the EU research project “FAST and efficient international disaster victim Identification” (FASTID) the Fraunhofer-Institute IOSB developed a software module for content based image retrieval. Given an input image, the aim of the software is to find those images within an image database which show the same object or scene as the input image.
The background of the software is to assist the identification of disaster victims in terms of effectiveness and speed. The part of the IOSB within the research project was to support the identification workflow by integrating automated image retrieval methods which operate on images of body modifications such as tattoos . This replaces today's manual classification of tattoos which is always subjective, time consuming and error-prone.
The basic algorithms of the system are however not restricted to images of tattoos but can be utilized in many other domains.
Parts of the system developed in FASTID have therefore been extracted leading to this CBIR software. This enables users to get an idea of the functionality and performance of the algorithms beyond the targets of research projects.
Both the generation of the image database and querying the database can be performed with any image data. Thus, the technology can be easily explored with respect to its applicability in various domains. The example image shows how the software is used to search a set of holiday images with a query image from the internet in order to find the holiday images of a distinct object (Golden Gate Bridge).
The research leading to these results has received funding from the European Union Seventh Framework Programme (FP7/2007-2013) under grant agreement no 242339.
 D. Manger, Tattoo Image Retrieval for Forensics. In 6th European Academy of Forensic Science Conference (EAFS2012).
 D. Manger, Content-based Tattoo Image Retrieval. In 21st International Symposium on the Forensic Sciences of the Australian and New Zealand Forensic Science Society (ANZFSS2012).
 D.Manger, Demo: A Tattoo Image Retrieval System, 2012 IEEE International Workshop on Information Forensics and Security (WIFS'12).