A HIGH RESOLUTION 3D TIRE AND FOOTPRINT IMPRESSION ACQUISITION DEVICE FOR FORENSICS APPLICATIONS

RUWAN EGODA GAMAGE, ABHISHEK JOSHI,

JIANG YU ZHENG, MIHRAN TUCERYAN

COMPUTER SCIENCE DEPARTMENT, IUPUI

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ACKNOWLEDGEMENT

This project was supported by Award No. 2010-DN-BX-K145, awarded by the National Institute of Justice, Office of Justice Programs, U.S. Department of Justice. The opinions, findings, and conclusions or recommendations expressed in this exhibition are those of the author(s) and do not necessarily reflect those of the Department of Justice.

Also thanks to Mr. Alan Kainuma for providing the test shoe.

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OBJECTIVES

• Acquire 3D depth images of tire and shoeprint impressions in a non-destructive way

• Simultaneously obtain a high resolution registered 2D color image

• Acquire long tire impressions in one scan (no stitching of multiple images necessary)

• Portable design and easy to use for outdoor capture

• Also scan shoes and tires themselves for matching purposes

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BASIC DESIGN OF THE HARDWARE

• Camera assembly moves at a precise and fixed speed along the rail.

• The slower it moves, the better resolution along rail direction (slowest speed: 1.3 mm/sec at 30 fps).

Control box

 

 

  

   

  

    

 

Power supply

HD camcorder

Red stripe laser light

 

Green stripe laser light

 

Actuator motion directionSpeed: 1-3mm/sec

Actuator rail: 1.75m long

 

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WHY TWO LASERS?

To be able to handle occlusions.

 

Green light occluded in this region,but red light visible.

Occluding surface

Scanner motion

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BASIC DESIGN OF DEPTH EXTRACTION

 

  

 

     

One line per video frame per laser One for red, one for green laser Depth variations on the surface

result in deformations in the laser line.o The amount of deformation is

used to estimate the depth values.

Depth values are calculated along the detected laser line.

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IMAGING GEOMETRY

In order to calculate depth from laser deformation in the image, we need to know the configuration of the camera and laser lights with respect to each other.

This can be estimated via a calibration procedure.

We do not want to perform calibration ahead of time, because the configuration can change during transportation or setup of the device.

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DEVICE CALIBRATION

Our device has a calibration procedure that is integrated with the scan.

Put calibration object (with known dimensions) into the scene and scan.

• The calibration is done as part of the post-processing.• Don’t worry about imaging geometry getting messed up

during transportation and set-up.

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CALIBRATIONIdeally the camera should be set orthogonal to the rail, but this is not realistic.

• We correct camera’s roll and tilt as part of calibration.

Coordinate systems defined for calibration:

 

 

X’

Y’

Z’

X

Y

Z

x

y

z

rail

X’Y’

Z’

XY

Z

xy

z

Camera coordinate system

After correcting roll and tilt

Rail coordinate system with respect to which all depth values are computed

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CALIBRATIONPlace an L-shaped calibration object with known dimensions in the scene

From the recorded video, select two images with lasers on the calibration object

Because of the linear motion along the rail, motion vectors of corner points in the FOV have a vanishing point p(x0, y0).

Compute vanishing point using corners of the calibration object to estimate tilt and roll of camera

• This is used to correct for tilt and roll of the camera.

A1B

1

C

1

D

1

E

1

F

1

L1 L3L

2

p(x0,y0)

A2B2 C2

D2E2F2

Calibration object

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CALIBRATIONLaser on L-shaped object

• Baseline length between two frames is known from the speed of rail motion and frame numbers (30 fps capture)

• 3D positions of corner points on a calibration object are captured using a user interface

Camera-laser relation

• Find the 3D laser lines on the calibration object to estimate the normal vector of the laser plane

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SOME EXAMPLE SCANS

Depth scan: depth color coded

2D color image acquired registered with depth image.

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SHOE SCAN

3D scan (pseudo-color) Color-texture image

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SCAN OF A SHOEDetecting fine details:

Shoe and desired features provided by expert

Features detected in our scan

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LONG TIRE IMPRESSION RESULTS

z range: 307.1mm-259.2mm. Brighter points are closer to camera

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ACCURACY

We did a systematic testing of the accuracy achieved in scanned images by designing and building a test object.

Accuracy Summary• Horizontal resolution

0.23mm (perpendicular to rail motion)

• Rail direction resolution ≥0.043mm

• Depth resolution ~0.5mm

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SOFTWARE USER INTERFACE

We built a software interface to perform metric measurements on the acquired image

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INTERFACES TO OPERATE THE DEVICEButton Interface

Programmed the motor to perform following

• Stop• Homing • Short Run • Long Run

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TABLET BASED WIRELESS INTERFACEBluetooth wireless Interface via tablet:

• more configuration options possible.

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CONCLUSION• Achieved 0.5mm depth accuracy.

• The prototype device is promising

• Accuracy can be improved by improving the subcomponents of the system or by improving the algorithms.

• Shoes and tires themselves can be scanned to be used for automated matching against a database or for computing degree of match results.