CORRELATION PROCESSING OF DIGITAL OPTICAL IMAGES FOR SOLVING CRIMINALISTIC PROBLEMS
https://doi.org/10.21122/2220-9506-2015-6-2-33-40
Abstract
The correlation processing of optical digital images of expert research objects is promising to improve the quality, reliability and representativeness of the research. The development of computer algorithms for expert investigations by using correlation analysis methods for solving such problems of criminology, as a comparison of color-tone image parameters impressions of seals and stamps, and measurement of the rifling profile trace of the barrel on the bullet is the purpose of the work. A method and software application for measurement of linear, angular and altitude characteristics of the profile (micro relief) of the rifling traces of the barrel on the bullet for judicial-ballistic tests is developed. Experimental results testify to a high overall performance of the developed program application and confirm demanded accuracy of spent measurements. Technique and specialized program application for the comparison of color-tone image parameters impressions of seals and stamps, reflecting degree and character of painting substance distribution in strokes has been developed. It improves presentation and objectivity of tests, and also allows to reduce their carrying out terms. The technique of expert interpretation of correlation analysis results has been offered. Reliability of the received results has been confirmed by experimental researches and has been checked up by means of other methods.
About the Authors
V. L. Kozlov
Belarusian State University
Belarus
Address for correspondence: Kozlov V.L. Belarusian State University, Nezavisimosty Ave., 4, Minsk, 220050, Belarus e-mail: KozlovVL@bsu.by
Belarus
Address for correspondence: Kozlov V.L. Belarusian State University, Nezavisimosty Ave., 4, Minsk, 220050, Belarus e-mail: KozlovVL@bsu.by
A. S. Vasilchuk
Belarusian State University
Belarus
Belarus
References
1. Yablokov N.P. Kriminalistika: priroda, sistema, metodologiceskiye osnovy [Criminalistics: the nature, system, methodological bases]. Moscow, Norma Publ., 2009, 288 p.
2. Vandler M.B. Primeneniye nauchno-tekhnicheskikh sredstv pri rassledovanii prestyplenij [Application of scientific and technical tools in the investigation of crimes]. St. Peterburg., 2000, 60 p.
3. Zubaha V.S., Ysov A.I. Species classification of computer-technical expertise. Ekspertnaya praktika. Moscow, EKC MVD RF, no. 48, 2000 (in Russian).
4. Bulgakov V.G., Kolotushkin S.M. Kompyuterniye tekhnologii v kriminalisticheskoj fotografii [Computer technologies in criminalistics photography]. Volgogrаd, 2000, 164 p.
5. Sutton M.A., Orteu J.-J., Schreier H. Image Correlation for Shape, Motion and Deformation Measurements. University of South Carolina, Columbia, SC, USA, 2009, 364 p.
6. Thorsten Siebert, Matt J. Crompton. Application of High Speed Digital Image Correlation for Vibration Mode Shape Analysis. Proceedings of the SEM Annual Conference June 7-10, 2010, Indianapolis, Indiana USA.
7. Im J., Jensen J.R. and Tullis J.A. Object-based change detection using correlation image analysis and image segmentation. International Journal of Remote Sensing, vol. 29, no. 2, 20 January 2008, pp. 399–423.
8. Okhandiara R.R., Rajub P.L.N., Bijkerc W. Neighborhood correlation image analysis technique for change detection in forest landscape. The International Archives of the 95 Photogrammetry, Remote Sensing and Spatial Information Sciences, vol. XXXVII, part. B8, Beijing 2008.
9. Bardachenko A.N. Features of the linear and angular measurements of the rifling traces on the bullets using modern microscopic equipment. News of Saratov University. New series. Ser. Economy. Management. Law. vol. 14, no. 1, h. 1, 2014, pp. 216–218 (in Russian).
10. Myron Z. Brown, Darius Burschka, Gregory D. Hager. Advances in Computational Stereo. IEEE transactions on pattern analysis and machine intelligence, vol. 25, no. 8, 2003, pp. 993–1008.
11. Szeliski R. Computer Vision: Algorithms and Applications. Springer, 2010, 957 p.
12. Horn B. Robot vision. MIT. Press Cambridge, MA, 1986, 503 p.
13. Wang S., Wang X., Chen H. A stereo video segmentation algorithm combining disparity map and frame difference 3rd International Conference on Intelligent System and Knowledge Engineering, vol. 1, 2008, pp. 1121–1124.
14. Ackermann F. Digital image correlation – performance and potential application in photogrammetry. Photogram Ree, 1984, vol. 11, 64, pp. 429–439.
15. William H. Press Numerical recipes in C: the art of scientific computing. Cambridge University Press, 2nd ed., 1995, 994 p.
16. Kenhi Ogawa. Optical distance measurement device using image sensors for determining distance to symmetric objects. Patent US, no. 5432594, 1995.
17. Kozlov V.L., Moroz I.A., Rybis A.S. Izmeritel’ rasstoyanii na cifrovoj fotocamere dlya criminalisticheskikh ekspertiz [Distances measuring instrument on a digital camera for criminalist examinations]. Patent BY, no. 8572, 2012.
18. Kozlov V.L., Vasilchuk A.S. Sub pixel image processing for distance measurement on the base of digital camera // Pribory i metody izmerenij. 2012, no. 1 (4), pp. 115–120 (in Russian).
19. Kozlov V.L., Rybis A.S., Ropot R.M. Ustrojstvo dlya sravneniya cifrovykh izobragenij ottiskov pechatej i shtampov dlya kriminalisticheskikh ekspertiz [The device for comparing of digital prints images of seals and stamps for criminal examinations]. Patent BY, no. 10722, 2015.
Review
For citations:
Kozlov V.L., Vasilchuk A.S. CORRELATION PROCESSING OF DIGITAL OPTICAL IMAGES FOR SOLVING CRIMINALISTIC PROBLEMS. Devices and Methods of Measurements. 2015;6(2):220-229. (In Russ.) https://doi.org/10.21122/2220-9506-2015-6-2-33-40
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