Automatic estimation of a scale resolution in forensic images
(2018) In Forensic Science International 283. p.58-71- Abstract
This paper proposes a new method for an automatic detection of a resolution of a scale or a ruler with graduation marks in the shoeprint images. The method creates a vector of the correlations estimated from the co-occurrence matrices for every row in a shoeprint image. The scale resolution is estimated from maxima in Fourier spectrum of the correlations’ vectors. The proposed method is evaluated on over 500 images taken at crime scenes and in a forensics laboratory. The experimental results indicate the possibility of applying the proposed method to automatically estimate the scale resolution in forensic images. The automatic detection of a scale resolution could be used to automatically rescale a forensic image before the printing... (More)
This paper proposes a new method for an automatic detection of a resolution of a scale or a ruler with graduation marks in the shoeprint images. The method creates a vector of the correlations estimated from the co-occurrence matrices for every row in a shoeprint image. The scale resolution is estimated from maxima in Fourier spectrum of the correlations’ vectors. The proposed method is evaluated on over 500 images taken at crime scenes and in a forensics laboratory. The experimental results indicate the possibility of applying the proposed method to automatically estimate the scale resolution in forensic images. The automatic detection of a scale resolution could be used to automatically rescale a forensic image before the printing this image in “one-to-one” scale. Furthermore, the proposed method could be used to automatically rescale images to an equal scale thus allowing to compare the images digitally.
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- author
- Gertsovich, I. ; Nilsson, M. LU ; Bartůněk, J. S. and Claesson, I. LU
- organization
- publishing date
- 2018-02-01
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- Gray level co-occurrence matrix, Near regular texture, Scale resolution estimation, Shoeprint image, Texture pattern periodicity
- in
- Forensic Science International
- volume
- 283
- pages
- 14 pages
- publisher
- Elsevier
- external identifiers
-
- pmid:29274623
- scopus:85038855166
- ISSN
- 0379-0738
- DOI
- 10.1016/j.forsciint.2017.12.007
- language
- English
- LU publication?
- yes
- id
- b427cc5f-5826-422c-ae1c-d3dccc43814b
- date added to LUP
- 2018-01-31 09:23:35
- date last changed
- 2024-01-29 10:58:39
@article{b427cc5f-5826-422c-ae1c-d3dccc43814b,
abstract = {{<p>This paper proposes a new method for an automatic detection of a resolution of a scale or a ruler with graduation marks in the shoeprint images. The method creates a vector of the correlations estimated from the co-occurrence matrices for every row in a shoeprint image. The scale resolution is estimated from maxima in Fourier spectrum of the correlations’ vectors. The proposed method is evaluated on over 500 images taken at crime scenes and in a forensics laboratory. The experimental results indicate the possibility of applying the proposed method to automatically estimate the scale resolution in forensic images. The automatic detection of a scale resolution could be used to automatically rescale a forensic image before the printing this image in “one-to-one” scale. Furthermore, the proposed method could be used to automatically rescale images to an equal scale thus allowing to compare the images digitally.</p>}},
author = {{Gertsovich, I. and Nilsson, M. and Bartůněk, J. S. and Claesson, I.}},
issn = {{0379-0738}},
keywords = {{Gray level co-occurrence matrix; Near regular texture; Scale resolution estimation; Shoeprint image; Texture pattern periodicity}},
language = {{eng}},
month = {{02}},
pages = {{58--71}},
publisher = {{Elsevier}},
series = {{Forensic Science International}},
title = {{Automatic estimation of a scale resolution in forensic images}},
url = {{http://dx.doi.org/10.1016/j.forsciint.2017.12.007}},
doi = {{10.1016/j.forsciint.2017.12.007}},
volume = {{283}},
year = {{2018}},
}