Image Background Matching for Identifying Suspects
Document Type
Conference Proceeding
Publication Date
2008
Abstract
Thousands of digital images may exist of a given location, some of which may show a crime in progress. One technique for identifying suspects and witnesses is to collect images of specific crime scenes from computers, cell phones, cameras and other electronic devices, and perform image matching based on image backgrounds. This paper describes an image matching technique that is used in conjunction with feature generation methodologies, such as the Scale Invariant Feature Transform (SIFT) and the Speeded Up Robust Features (SURF) algorithms. The technique identifies keypoints in images of a given location with minor differences in viewpoint and content. After calculating keypoints for the images, the technique stores only the “good” features for each image to minimize space and matching requirements. Test results indicate that matching accuracy exceeding 80% is obtained with the SIFT and SURF algorithms. Abstract © Springer
DOI
10.1007/978-0-387-84927-0_24
Source Publication
IFIP — The International Federation for Information Processing, vol 285
Recommended Citation
Fogg, P., Peterson, G., & Veth, M. (2008). Image Background Matching for Identifying Suspects. In Advances in Digital Forensics IV. DigitalForensics 2008 (IFIP vol 285, pp. 307–321). Boston: Springer. https://doi.org/10.1007/978-0-387-84927-0_24
Comments
The "Link to Full Text" on this page loads the PDF of the paper, furnished through the Springer Nature SharedIt content-sharing initiative. The publisher retains permissions to re-use and distribute this chapter from IFIP vol. 285.
© IFIP International Federation for Information Processing 2008