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5METHODS TO IMPROVE THE INPUT IMAGES IN FINGERPRINTING
Abstract
This article presents a method of improving the quality of digital picture processing of scans of comb fingers and toes during forensic identification using fingerprinting. It was determined number of advantages of digital scanner Futronic's FS80 and ways to improve the quality of scans obtained by converting raster prints into vector graphics using the algorithm VeriFinger 6.6/MegaMatcher 4.4 Identification Technology Algorithm.
Keywords
identification of the person, fingerprinting, dermatoglyphics
AUTHORS
Natalia Kozan
PhD, Associate Professor Ivano-Frankivsk National Medical University Ivano-Frankivsk, Ukraine NMKozan@gmail.com
Yulia Kotsyubynska
Assistant of a lecturer Ivano-Frankivsk National Medical University Ivano-Frankivsk, Ukraine Ko tsyubynska YZ@gmai l.com
The rapid development of modern technology, particularly related to different industry sectors, entails a number of negative consequences, such as natural disasters, plane crashes, human-made disasters, military conflict that is causing massive loss of life (Horbunov, Klak, Shekhovtsova, 2012). The result of the above events is the depersonalization of dead persons related to disfiguration of face, dismemberment, injury, burning of bodies and its putrification. In this regard, the primary issue that arises during operative-investigation is to identify individuals (Seema, Mahajan, Gandhi, Singh, 2012). Dermatoglyphics offers a quick and inexpensive identifying of an unknown person. In the practice of forensic medicine dermatoglyphics has been recently used in the examination of disputed paternity, but during the last decades it has also been actively used in the study of family kinship with the further use of the data for the identification of unknown persons using dermatoglyphics parameters of relatives (Zvyahyn, Mazur, Voroshilov, Ahmedyn, 2008). It is important to note that the most completely problem of family ties, ethnic and racial territorial variability of dermatoglific parameters is considered in methodological works based on a study of the main palmar lines, dermatoglyphics signs of feet, papillary drawings of distal phalanges of the fingers and toes and middle phalanges and basic phalanges of fingers (Abue, 2013; Andreeva, 2012; Deepa, 2014; Horbunov, 2012; Mishagin, 2010; Seema, 2012; Shpak, 2013).
There are many methods for studying dermatohliphic skin relief. The method of obtaining dermatoglyphics prints is not convenient in use due to contamination of the extremities with ink, the quality of the resulting prints are not always satisfactory, requiring repeat of the procedure and entails additional time; there are also disadvantages associated with the processing of the results and the creation of digital archives. For the improvement of this method a number of researchers offered to carry out digitization of obtained finger prints on paper through scanning. Images obtained by scanning may be distorted due to background effects caused by uneven application of turning the substance, uneven illumination of the object surface, structure of paper, noise of recording equipment, scanning equipment noise, quantization noise during digitization
image (Dmitriev, 2006). Using a computer for further image processing reqiresobtaining dermatoglific prints in high quality, aims avoiding further errors in the calculation (Azazy, 2011). To facilitate the task which is set to the researcher and to improve the quality of received images we propose to use the scanner Futronic's FS80 USB 2.0. Images obtained by the scanner Futronic FS80, usually are of high quality and allow to estimate the characteristics of papillary picture precisely. But due to skin lesions of investigated fingers, operator error and other unforeseen circumstances, there is a need for additional image processing.
In our work with purpose of improving the image quality we use superior Fingerprint identification algorithm (FIA). The main objective of this software is to convert raster images into vector. When using this procedure there is possibility of misinterpretation of the data of pixel matrix, so the choice of algorithm (or software) that is right for processing photos with papillary pattern is extremely important. (Pic. 1).
In general software algorithm that is used for turning raster image to vector (of different detalization stages) can be implemented on different programming languages. Therefore, we use code created on C++. The simplest implementation on this language can be presented as few simple actions. Let we have pixel p which is contained into massive of data N*M.
FIGURE 1. THE RESULTING VECTOR DRAWING OBTAINED BY FIA
We can present it as
{X, y - coordinate distance
f - square of Euclidean distance}
to form an array of parameters we enter parameters for white pixel: x = y = 9999 f = 9999 * 9999 for white - x = y = f = 0
In each pixel, there are 8 neighboring pixels which we enumerate as follows: 2 3 4 1 p 5 8 7 6
Then we introduce the auxiliary functions h and h G. function determines the Euclidean distance between adjacent pixels, and the function G calculates a new value for the distance components.
h (p, q)
{If q - 1 or 5 neighbor {return 2 * q.x + 1} if q - neighbor 3 or 7 {Return 2 * q.y + 1} in other cases {return 2 * (q.x + q.y + 1)}} G (p, q)
{If q - 1 or 5 neighbor {return (1, 0)} if q - neighbor 3 or 7 {return (0, 1)} in other cases {return (1, 1)}}
Perform first pass through pixels in a direct manner.
For each pixel p {for every neighbor q from 1 to 4 {if (h (p, q) + qf <pf) {pf = h (p, q) + qf (px, py) = (qx + qy) + G (p, q)}}}
Similarly we conduct pass in reverse order. Then the algorithm must be repeated for the negative image and calculate the distance between pixels in both images of received cards and combine them.
d1 = sqrt (p1 .f + 1); d2 = sqrt (p2.f + 1); d = d1 - d2; received cards minus from each other and get a vector map.
For their research, we use the improved FIA (VeriFinger SDK like improved code). Currently, there is a wide range of different software that allows to improve images quality. The most common and powerful tool in the processing of digital images is a product suite of adobe - Adobe Creative Cloud. In our work we use Photoshop CC and Illustrator CC. In these programs there is great number of tools that allow to improve image quality in a particular case, but usually satisfactory result requires using several of them - increase (decrease) the contrast, coverage, focus, etc. For these actions built-in functions in the Editor are usually enough (Pic.2).
FIGURE 2. PROCESSING OF MATERIALS IN ADOBE ILLUSTRATOR CC
Purpose of improving image quality is to get reliable data for further statistical analysis. Scientists solve the problem of data processing in different ways, but in most cases this stage is reduced to filling base of data, its structure and formalization with further processing in programs for statistical analysis.
In their studies, we use algorithms developed based on Microsoft Excel and the software package STATISTICA. Dermatoglyphics data of one person can be represented as a table with more than 30 significant features (Pic.3).
№ Type of pattern left hand right hand eft Dot
1 2 3 4 5 1 2 3 4 5 l f
1 LU A A LU W LU LU LU LU LU ..n
2 LU LU LU LU LU LW LU LU W LU ..n
3 A W- A LU LU LU W m LU W . LU Ä..n
4 LU A \ A LU W LU LU \ LU LU LU .n
..N ..n ..n \.n ..n ..n ..n ..n ^ ..n ..n ..n
left h\nd righ\ hand
A LU LR N W LW A LU LR W 1 LW .. N
2 2 0 \1 0 0 5 0\ 0 0 .. n
0 5 0 0 0 3 0 N 11 1 .. ni
2 2 0 A 0 0 3 0 1 0
2 2 0 0 0 5 0 / 0 r ..n
..n ..n ..n ..n > v ..n ..n ..n ..n f ..n
W L N
height (W + (LU + LU LR ^LW
.W) LR)
165 4 10 6^ s2 1/
172 2 15^ 15
168 T6 À 6 8 ► 2
165 4 10 6 8 2 1 3
..n ..n ..n ..n ..n ..n ..n ..n
FIGURE 3. A SIMPLIFIED SCHEME OF DERMATOGLIFIC STRUCTURING DATA
After processing the initial data we get tables with approximately one hundred columns which describe characteristics derived from these values and results of mathematical calculations. Therefore, it is reasonable to partition data into component parts, which are recorded in various tables with linked macros (software algorithm). Separation of data is convenient also because in future they need to be transferred into the program of statistical analysis which uses mainly not outcoming (obtained directly from papillary pattern) but the resulting data. Also structuring data allows to make easier the evaluation of statistical dependencies that are difficult to be recognized in large arrays of data.
Conclusions. Thus, improving the method of receiving prints of comb fingers and toes (when using the scanner Futronic's FS80), as well as digitizing the data using a digital method (algorithm VeriFinger 6.6 / MegaMatcher 4.4 Identification Technology Algorithm), and improving the quality of the obtained scans (using prints transforming raster to vector graphics) will allow to improve the objectivity and evidency of forensic medicine with purpose of identifying person.
REFERENSES
1. Abue A.D., Ujaddughe M., Kpela M.T., Abuel A.D. (2013) "The Arch Pattern Dermatoglyphics on the Toes of Hausa Ethnic Group of Nigeria", Advances in Anthropology, Vol. 3(4): 237-239.
2. Andreeva A. (2012) "Fenetyc population characteristics Yakutia (by Features dermatohlific drawings)", International magazine of experimental education, 4: 77-78.
3. Azazy A.A. (2011) The image processing system in the diagnosis of hereditary diseases on a method dermatoglyphics: avtref. diss...PhD, Vologda, 16 p.
4. Deepa D., Chandra P., Ishwer T. (2014) "A Study of Fingerprint in Relation to Gender and Blood Group among Medical Students in Uttarakhand Region", J. Indian Acad. Forensic Med., January-March 2014; Vol. 36(1): 23-27.
5. Dmitriev A.V. (2006) "Recognition dermatoglyphics signs of neurogenic based networks", Proceedings TRTU, 2006, p.74-78.
6. Horbunov N.S., Klak N.N, Shekhovtsova Y.A. (2012) "Prognostic dermatoglific possible signs of human", Herald of new medical technologies, 4 p.
7. Mishagin V.P., Zoroastrov O.M. (2010) "Forensic aspects of regional dermatoglific characteristics". Medical science and education in the Urals. №1:112-114.
8. Seema, Mahajan A, Gandhi D, Singh M. (2012) "Dermatoglyphics - Study and Review of literature", Novel Science International Journal of Medical Science, 1 (6): 191 -198.
9. Shpak L.Y. (2013) "On the classification of finger patterns. Bulletin of Anthropology". Science Almanac. 2 (24):132-140.
10. Zvyahyn V.N., Mazur E.S., Voroshilov N.S., Ahmedyn R.L. (2008) "Discriminant canonical analysis ethno-territorial polymorphism in Example contrast ethnic groups", Journal of Tomsk state-owned University, 309: 115-117.
COMPETENCE-ORIENTED ASSIGNMENTS IN THE TEACHING CONTENT OF ENGLISH LESSONS AT THE UNIVERSITY
Abstract
The article discusses the examples of competence-oriented assignments which were used at English lessons at the Economics University as a means to develop and assess competences of economics students. Their structure and content are analysed. Constructed on the basis of professional tasks of economists competence-oriented assignments serve as the resource to renew the content of English lessons and implement the function of English language as a means for the purposeful development of professional competence.
Keywords
competence-oriented assignments, professional tasks, competence, foreign language
AUTHOR
Ludmila Maslova
PhD student, Department of Pedagogy Herzen State Pedagogical University of Russia Saint Petersburg, Russia lsm-2003@list.ru
The implementation of the competence-based approach in education involves changing the views on the educational outcomes. The implementation requires creating fundamentally new training and methodological resources (courseware), the box of evaluation tools, in particular, to measure the results through the integrated development of competencies.
