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Forensic Applications of Computer Vision Peter Kovesi Department of Computer Science & Software Engineering The Uni

Forensic Applications of Computer Vision Peter Kovesi Department of Computer Science & Software Engineering The University of Western Australia. Application areas Image enhancement Image metrology Biometric identification. Image Enhancement

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Forensic Applications of Computer Vision Peter Kovesi Department of Computer Science & Software Engineering The Uni

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  1. Forensic Applications of Computer Vision Peter Kovesi Department of Computer Science & Software Engineering The University of Western Australia

  2. Application areas • Image enhancement • Image metrology • Biometric identification

  3. Image Enhancement Video surveillance images are typically of poor quality camera video recorder monitor The quality of the display on the monitor can be misleading. The video recorder runs 24 hours/day.  The tape gets worn and the recording heads get dirty.  The images that are recorded can be very poor.

  4. Image Enhancement • Common problems in images : • Poor resolution, especially in video images. • Poor contrast due to under or over-exposure. • Corruption with noise. • Motion blur or poor focus. • Misalignment of rows from line jitter and interlacing of motion in video images.

  5. Poor resolution: Zooming in does not help!

  6. Create a `higher resolution’ image by mathematically interpolating pixel values

  7. Super-resolution from multiple low resolution images Images must be aligned accurately. Object should be planar. Irani and Peleg 1991 Capel and Zisserman 1998

  8. Super-resolution from multiple low resolution images: Results from synthetic data can be impressive

  9. Real data: Car number plate - low resolution + blur and noise.

  10. Super-resolution from multiple low resolution images: Number plate reconstruction

  11. Denoising Current method of choice is wavelet shrinkage denoising. Donoho and Johnson 1995 original image

  12. Denoising Grey scale enhanced image

  13. original deinterlaced wavelet denoised and contrast enhanced

  14. original deinterlaced wavelet denoised and contrast enhanced

  15. Image Metrology Calibration targets allow views of flat surfaces to be rectified. Rectified views allow measurements to be taken.

  16. Image Metrology Rectified views of the fence and ground. Criminisi, Reid and Zisserman 1999

  17. If a 3D calibration frame is placed in a scene and photographed from two or more directions 3D measurements can be made. Image Metrology However, care is needed to get accurate results.

  18. Image Metrology Stereo reconstruction 3D Measurements can be taken from the photographs long after the scene has been destroyed.

  19. Image Metrology Some measurements can be made in an uncalibrated image if you can determine vanishing points and the horizon.

  20. An unknown height can be determined if you know the horizon, the vertical vanishing point and a reference height. Criminisi, Reid and Zisserman 1999

  21. Conclusion Advances that have been made in Computer Vision, Photogrammetry and Projective Geometry over the last 10 years provide new opportunities for forensic science.

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