Image processing and super resolution methods for a linear 3D range image scanning device for forensic imaging
Abstract
In the last few decades, forensic science has played a significant role in bringing criminals to justice. Shoe and tire track impressions found at the crime scene are important pieces of evidence since the marks and cracks on them can be uniquely tied to a person or vehicle respectively. We have designed a device that can generate a highly accurate 3-Dimensional (3D) map of an impression without disturbing the evidence. The device uses lasers to detect the changes in depth and hence it is crucial to accurately detect the position of the laser. Typically, the forensic applications require very high resolution images in order to be useful in prosecutions of criminals. Limitations of the hardware technology have led to the use of signal and image processing methods to achieve high resolution images. Super Resolution is the process of generating higher resolution images from multiple low resolution images using knowledge about the motion and the properties of the imaging geometry. This thesis presents methods for developing some of the image processing components of the 3D impression scanning device. In particular, the thesis describes the following two components: (i) methods to detect the laser stripes projected onto the impression surface in order to calculate the deformations of the laser stripes due to 3D surface shape being scanned, and (ii) methods to improve the resolution of the digitized color image of the impression by utilizing multiple overlapping low resolution images captured during the scanning process and super resolution techniques.
Degree
M.S.
Advisors
Tuceryan, Purdue University.
Subject Area
Criminology|Computer science
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