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Krystyn Łuszczuk, M.Sc. Eng. IT specialist, member of the Polish Forensic Association Mieczysław Goc, Ph.D. (corresponding author) Professor at the WSB University in Gdańsk, Deputy President of the Polish Forensic Association Andrzej Łuszczuk, M.Sc. Document expert at the Polish Forensic Association

Use of scangraphy for computer visualization of handwritten text shading

Summary

The article indicates the importance of computer programs as tools supporting the handwriting expertise and increasing its objectivity. Some of these programs are based on computer scangraphy. Scangraphy is a handwriting examination method in which a text sample is treated as a raster image (a bitmap), i.e. a set of single (dots) pixels. The bitmap pixel pattern can be tested in a variety of different ways, as required. The article describes the first computer program to use scangraphy in handwriting examination. Key words: scangraphy, handwriting, computer handwriting scans, SCANGRAF

Introduction of expert opinions, particularly vivid in the doctrine Studies on handwriting are mainly based on qualitative and American jurisprudence, not always favorable to methods. Quantitative methods, consisting of different the handwriting expertise, often classifying it as the types of measurements, instrumental analyses and so-called non-scientific evidence, has led, on the one statistical calculations, which guarantee high precision hand, to the development of criteria for the admissibility and repeatability of results, have a minor usage. Due to of such evidence in court proceedings2, and, on the limited role of measurements in handwriting expertise, other hand, to the initiation of studies on the actual subjective evaluation of test results by an expert is of state of handwriting expertise, including the relevant key importance1. Such an evaluation is based on the methodology and, above all, to the development of new, expert’s experience, knowledge and qualifications and, more objective test methods, based, among others, on therefore, its results are frequently not as unambiguous computer techniques3. However, this does not mean as in the case of quantitative methods (Moszczyński, that traditional methods of handwriting examination 2011, pp. 126-138). This feature of the handwriting have no scientific basis. Their scientific character has examination was the main argument raised by critics been confirmed both by many years of expert practice of handwriting expertise, who allege that this method and by the opinion of the vast majority of authors of has an inadequate level of metric characteristic scientific publications on this subject4. Undoubtedly, the determinants, is intuitive and subjective with regard to identification. The discussion on the scientific character 2 The most popular are the so called Daubert’s standards. 3 These issues are presented, among others, in the 1 This aspect of the handwriting opinion has been pointed monograph of M. Goc (2016). by many authors, including W.R.Harrison, who, as early as 4 The issues related to the scientific basis of handwriting in the 1950s, wrote that handwriting comparative analyses expertise, together with the criticism of the position which are to a large extent subjective, which exposes them to undermines the possibility of issuing categorical opinions misinterpretations. (Harrison, 1958, p. 342). Cf. also Widła, and the simultaneous indication of the scale and causes 1982, pp. 83–96; Hecker, 2000, p. 193; Kwiatkowska- of errors in handwriting expertises, are comprehensively -Wójcikiewicz, Wójcikiewicz, 2010, pp. 319–328; Mosz- presented in the monograph cited above Goc, 2016, czyński, 2011, pp. 126–138. pp. 47–106).

ISSUES OF FORENSIC SCIENCE 300(2) 2018 55 FORENSIC PRACTICE introduction of computer technology in the handwriting Table 1. Handwriting parameters tested by GLOBALGRAF expertise in the last years constitutes an important step package. towards increasing the method’s objectivity. Computer techniques significantly reduce the subjectivity factor, GLOBALGRAF but do not eliminate it completely. The final handwriting identification decision is left to the discretion ofthe Lp. Program Parameters tested expert, while the task of the computer programs is to Shape coefficient facilitate the expert’s decision. Computer programs facilitating handwriting examination have been 1. GRAPHOTYPE Size ratio used for several years abroad, as well as in Poland. Graphotype A team of experts of the Polish Forensic Association in cooperation with academic staff of the University of Kinetic-Geometric Probability Warsaw and experts of the Central Forensic Laboratory Index 2. KINEGRAF of the Police within the framework of development Identification value of the 5 projects financed by the Ministry of Science and handwriting sample Higher Education (MNiSW) and the National Centre for Research and Development (NCBiR) developed Linearity coefficient two packages of computer applications supporting Angular similarity coefficient handwriting examination. The first package called GLOBALGRAF consists of four computer programs: 3. RAYGRAF Morpheme density factor GRAFOTYP, KINEGRAF, RAYGRAF i SCANGRAF. Letter density coefficient These programs are already being used in expert practice and receive a positive feedback. The second Impulse factor package, GLOBALGRAF II, was completed in 2016 and includes four additional programs: BARWOSKAN, CENTROGRAF, LINIOGRAF and PROFILOSKAN. because this program has nothing to do with These programs use two basic test methods, i.e. graphometry, as it does not measure any parameters, computer graphometry6 and scangraphy7. but is used to visualize the pressure (shading system) in the scripts examined. For this purpose, it uses the Computer graphometry scangraphy method mentioned in the introduction. As the name suggests, graphometry tests the basic, geometric parameters of handwriting, such as lengths, Scangraphy widths, angles of inclination, curvature, surfaces, Scangraphy is the result of a search for a test method densities and impulses. Once tedious and time- that would allow to study and compare the features of consuming (carried out manually on the enlarged handwriting resulting from an uncontrolled writing habit script images), these measurements do not pose any (without the consciousness of the writer) and, at the major problems after the introduction of computer same time, characterized by a relatively high level of techniques. Moreover, computer technology allows individualization and graphokinetic stability. According the implementation of new parameters, which are to handwriting experts, such a feature, difficult to mathematical transformations of basic parameters. imitate, is shading and pressuring of handwriting, where The table below shows the handwriting parameters scangraphy can be the method of choice to facilitate tested by the aforementioned GLOBALGRAF package. comparative analysis of this feature. Scangraphy It is easy to notice that Table 1 lacks the fourth breaks with the traditional perception of handwriting program of the package, namely SCANGRAF. It is from the perspective of its graphicism. A text sample is treated as a bitmap, which undergoes a cyclical transformation revealing the distribution of pressure 5 (cf. Development Project No. OR 00003807 “Development over the surface underneath the writing instrument of methodology and programs and construction of (Łuszczuk, Łuszczuk, 2012, p. 226). a workstation for identification of handwriting and signatures Scangraphy assumes the principle (already verified using computer graphometry” (completed on 8 July 2011) in expert practice) that the phenomenon of “shading” and Development Project No. DOBR-BIO4/038/13297/2013 occurring in a handwritten document is the result of “Measuring tools to support handwriting and signature changing pressure exerted on the surface by a writing analysis” (completed in December 2016). instrument, causing some of the drawn lines to be more, 6 Computer graphometry – a term proposed (A. Łuszczuk, K. Łuszczuk) at the 5th Forensic Seminar in May 2009 in while other to be less saturated, depending on the Ciechocinek. pressure. Scangraphy is a colorimetric method which 7 The test method proposed by A. Łuszczuk and K. Łuszczuk does not test the so-called graphism of handwriting in June 2010 at the 14th Wrocław Symposium for as such, but the colour content of a raster image Handwriting Examination. (a photographed or scanned writing sample). Such

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Fig. 1. A – Signature sample, B – Enlarged fragment showing the pixel structure.

a digital sample image, composed of single (dots) pixels ranging between 0 (lack of component) and 255 is called a “bitmap”. Each digital image, obtained from (maximum saturation). Figure 2 summarizes some a scanner, a digital camera or a camcorder, represents examples of pixel colour determination according to a collection of such points (pixels), whose number the RGB colour model. depends on the so-called resolution of the recording Scangraphy enables qualitative and quantitative device8 (digital camera, camcorder, scanner, etc.). The analysis of the bitmap’s colour structure. It allows to pixel structure of a digital image becomes visible when test each pixel’s RGB, change the colour values of zooming in. The higher the resolution of the output the components, invert and convert the image, and image, the greater the magnification required to make compare brightness between pixels in the same bitmap the pixel structure visible. Above, in figure 1, a sample as well as between two different bitmaps. of the signature and its enlarged part with a visible pixel Inversion (from positive to negative) consists of layout are shown. converting the RGB values into new values that add up Understanding scangraphy (and the programs to the maximum saturation of 255, so that each original based on this method) makes it easier to understand pixel with a Porig(RGB) component is converted into the basic principles of digital colour recording, which Pinv (255 – R, 255 – G, 255 – B) pixel. For example, the are set out below. original Porig pixel (124, 72, 83) of the dark pink colour

will have the Pinv components (131, 183, 172) after Additive digital colour recording method inversion and will become greyish-blue green. Inversion In digital technology there are many methods of colour as a method has been known for years in photography recording. The main of these are: (both colour and black-and-white) and often used also –– RGB (red, green, blue) – additive method, in forensic photography. –– CMYK (Cyan, Magenta, Yellow, Black) – Conversion (replacement of a colour image to subtractive method, black-and-white) is a method similar to inversion. –– HSB (hue, saturation, brightness). Our considerations will be limited to the first of the abovementioned methods as the most popular method in digital technology. In this technique, the colour Pixel components Pixel colour of each pixel in a bitmap is described by three basic RGB colour components (the so-called additive method): –– red component – (R-red), 255 255 255 White –– green component – (G-green), 0 0 0 Black –– blue component – (B-blue). According to this method, each pixel is characterised 128 128 128 Grey by P data (R, G, B), wherein the R, G, B values indicate 255 0 0 Red the degree of saturation of the colour components, 0 255 0 Green 0 0 255 Blue 8 Resolution is a characteristic feature of digital images as well as of the devices used to display or register them 255 255 0 Yellow (cameras, camcorders, scanners, televisions, monitors, displays, etc.). It is defined (in pixels) by giving the dimension 159 122 56 Pale brown of a digital image, either in the form of the product (width × height), e.g. 1024 × 678, or as a numeric value of that Fig. 2. Examples of pixel colour determination according product, in this example 694 272 pixels. to the RGB colour model.

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Basically, it consists of averaging the saturation of the RGBavg is simply calculating the arithmetic mean of colour components of an output pixel and assigning the colour component values and assigning each the converted pixel equal, averaged components. component a calculated, identical mean value. In

Thus, the originally dark brown pixel Porig(48, 34, 2), practice, RGB averaging is de facto a conversion of after averaging the components [(48 + 34 + 2)/3 = 28], colour into its black-and-white equivalent. An example becomes the converted, monochromatic pixel Pconv of RGB averaging is shown below in figure 4. (28, 28, 28), very close to black (Łuszczuk, Łuszczuk, Figure 4 shows two colours: A (blue shade 2012). with RGB (91, 155, 213) and B (green shade with Inversion or conversion of the whole image (bitmap) RGB (97, 180, 137)). By judging on the basis of the is a transformation of each pixel of the image into three RGB components, it is impossible to determine a different one, according to the rule described above. which of these colours is darker. After averaging

Without a computer, such inversions/conversions (also (conversion), the colour A turns grey with RGBavg(153) called transformations) would be impossible. The and the colour B turns grey with RGBavg(138). As the duration of the entire process varies from a few up to RGBavg(138) is smaller than the RGBavg(153), it can be several dozen seconds, depending on the number of unequivocally concluded that the colour B is darker pixels in the bitmap, i.e. on the resolution of a scan than the colour A. or a photograph, as well as the parameters of the There are practical benefits to this. It is possible computer’s processor and operating system (Łuszczuk, to compare two bitmaps, which correspond to two Łuszczuk, 2012). handwritten samples verified for identity. It is also Below are examples of inversions and conversions. possible to check whether the pixel colour pattern is similar or different at the same topographic locations of the samples. With this knowledge, it can be relatively Original images Inversion Conversion easily determined whether the pressuring parameter is identical between both samples. The consistency of pressuring and shading parameters is an important factor in making a decision about the identity of the scripts compared.

Transforming bitmaps as a method to visualize shading (pressure) The first step of the shading visualization is to search

Fig. 3. Examples of inversions and conversions the sample bitmap, based on the RGBavg, for the darkest

of digital images. pixel with the lowest RGBavg value. This pixel is usually situated within the graphical line of the script under examination (see point marked “1” in fig. 5). Then, by Comparing pixel brightness in a digital image – comparing all the pixels of the bitmap, the brightest average RGB pixel, RGBavg/max, is found, which is located on the border It is practically impossible to compare the colour between the graphic line and the background, or within brightness between pixels (to determine which is the background. The brightest pixel is indicated by the lighter and which is darker), assuming that each pixel number “5” in figure 5. has three colour components. It would mean that The colour difference between the brightest and the the values of all three components, including their darkest pixel constitutes the colour range of the ink combinations amounting to approximately 17 million used to draw the graphical line. colour shades would have to be compared at the same Colour range = RGB – RGB time. It is worth keeping in mind that when dealing avg/max avg/min with the additive method and the so-called 24-bit In the example given in figure 6, the colour range is color depth9 (which is the case here) there is just such 220 – 63 = 157. Then the range is divided into several a number of color shades. A possible solution is to intervals, in this particular example, seven intervals compare average RGB values (marked as RGBavg). with the spans 157/7≈22. A single interval is called the “iteration step”. Next, the intervals, starting from the brightest one, are subjected to transformations in 9 24-bit color depth means that each colour component subsequent repetitions (iterations). Transformations (color channel) is stored on 8 bits, which, in the case of consist of converting the colour of the pixels from three channels, amounts to 24 bits. Since the maximum number 11111111 in binary format or 255 in decimal a given interval to a colour of the user’s choice (default: format can be written on 8 bits or 1 byte, the number of white), which gives the impression that the pixels are possible colour combinations at this bit depth equals being removed from the bitmap, whereas, in fact, they 2563 = 16 777 216 colours. In different applications, different only change their colour to white. The transformation colour depths can be found, e.g. 8-bit, 16-bit, 32-bit, etc. iterations are shown below.

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Conversion (colour averaging): RGB (91, 155, 213) RGBavg (153) (91 + 155 + 213) / 3 = 153 converts RGB (91, 155, 213) to average A → RGB (153, 153, 153), →

what is abbreviated as RGBavg (153)

Conversion (colour averaging): RGB (97, 180, 137) RGBavg (138) (97 + 180 + 137) / 3 = 138 converts RGB (97, 180, 137) to average B → RGB (138, 138, 138), →

what is abbreviated as RGBavg (138)

Fig. 4. Example of colour conversion for the purpose of RGBavg estimation.

As the number of iterations increases, the lighter intervals gradually disappear (in fact, they turn white), while the darker ones remain, visualizing the ink distribution (shading system) within the graphic line of the handwriting sample. In figure 6, the image “A” is the initial appearance of the signature sample. Transformations of the first and second iterations (“B” and “C”) “remove” the grey background of the sample. Five consecutive transformations, from “D” to “H”, allow to visualize the shading system or, in other words, to determine, in which parts of the graphic line the pressure of the writing instrument was the strongest. Increasing the number of iteration Fig. 5. The darkest and brightest pixel intervals decreases the “iteration step”, which has the of a signature sample bitmap fragment.

Removed interval 220–198 Removed interval 197–175

Removed interval 174–152 Removed interval 151–129 Removed interval 128–106

Removed interval 105–83 Removed interval 82–65

Fig. 6. Transformations of the signature bitmap in seven iterations.

ISSUES OF FORENSIC SCIENCE 300(2) 2018 59 FORENSIC PRACTICE advantage that the differences between the images of subsequent transformations will be more subtle, smoother, without radical changes. When increasing the number of iterations, it is also important to ensure that the excessive number of iterations does not lead to the complete disappearance of the graphic line. Simultaneous transformation carried out on the two samples compared allows to confirm or exclude their identity. In order to carry out all these scangraphical transformations, it is necessary to use an appropriate computer application (SCANGRAF), which will perform the operations described above on the samples to be tested and visualize the shading systems, thus enabling the assessment and verification of their identity (http:// kryminalistyka.pl/program-globalgraf/, accessed on: 22.11.2016). Fig. 7. SCANGRAF start page. SCANGRAF – application for visualization of the shading system SCANGRAF, as suggested by its name. is a program After pressing the “Start” button, another window is that uses the scangraphy method in handwriting displayed – the program’s main interface – as shown examination. It enables visualization of the shading in figure 8. system in one or, as a standard, two text samples The program makes it possible to select one of four (signatures) at a time. This concomitance allows the sample view options, prepared automatically by the expert to make a quick and effective comparison of the computer, without user intervention, when opening the shading systems in the texts analyzed. Figure 7 shows sample. These options include: the original image, the the program’s title/start page. coloured negative, the black-and-white positive and

Sample rotation buttons

Sample scaling buttons

Adopted transformation parameters

Fig. 8. SCANGRAF main window (interface) with empty sample windows.

60 ISSUES OF FORENSIC SCIENCE 300(2) 2018 FORENSIC PRACTICE the black-and-white negative. The user selects one of the view options, depending on the specific test circumstances. General instructions for using the view options are as follows: –– for most of the test circumstances (dark ink on a light background in both samples) the original images of both samples should be chosen; –– for samples with similar ink intensities but different colours (e.g. red and green), it is preferable (optionally) to analyze images transformed Fig. 9. Dialog box for setting the image transformation into black-and-white positives, whereas when parameters for sample A. dealing with light ink colour, good visualization results can be obtained by transforming into the coloured or black-and-white negative; In this window the program indicates the colour –– in occasional cases (e.g. where one sample is range (determined at the time of opening the sample), a light inscription on a dark background, whereas the default number of iterations (repetitions) and the the other represents a dark inscription on a light resulting default iteration step. The iteration step is background), it is not possible to analyze the expressed as the integer rounded quotient of the color original images. In this case, one of the samples range by the assumed number of iterations. In this must be converted into the coloured or black- exemplary window, an iteration step of 10 results from and-white negative, followed by analysis being the rounded division of the colour range of 205 by the carried out in the same way as for the originals. default iteration number of 20. Once the default values However, the visualization result should be proposed by the program have been accepted, the user interpreted in the opposite way, i.e. in a positive should press the “OK” button and continue working. image, a strong pressure is represented by the However, if the user does not want to use the default dark colour, while in a negative image, by the parameters, the desired number of iterations can be light colour. set by overwriting the blue highlighted default number After opening a sample marked “A” and pressing of 20. The new number must lie within the range 2-40 the ‘Default’ button, a dialog box appears, in which the (entering a number that does not fall within this range will transformation parameters should be set as follows: generate an error message). After entering the number of iterations selected by the user, the program adjusts the appropriate iteration step value. The higher the

Fig. 10. SCANGRAF interface with signature samples before commencing analysis.

ISSUES OF FORENSIC SCIENCE 300(2) 2018 61 FORENSIC PRACTICE number of iterations selected, the smaller the iteration worth to make sure that the product of the number of step will be adjusted, to maintain smooth changes in iterations and the iteration step does not exceed the the appearance of the graphic line during subsequent colour range. If this happens, the image transformation transformations, as discussed earlier. However, the of the last iteration will cause the graphic line to increased number of iterations will increase the time of completely disappear. Although this is not a substantial analysis, which in the case of processing large sample error, it will make the last transformation unnecessary files (especially those in “tif” format), may be irritating and useless. A similar selection of parameters can be to the user. Choosing own number of iterations, it is made after opening a second sample marked “B”. It

Fig. 11. Sample images after the fifth transformation (grey background partially removed).

Fig. 12. Sample images after the eighth transformation (background removed, visible shading differences).

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Fig. 13. Sample images after the twelfth transformation (distinct shading discrepancies).

is worth noting that the transformation parameters of been determined, a further step in the analysis can be both samples should not be (and in fact, are generally taken. Pressing the “Transform” button for one or the not) identical. They should be determined on a case- other sample results in the execution of the first image to-case basis by the expert carrying out the analysis. transformation of the selected sample. Each time this Therefore, once both samples “A” and “B” have been button is pressed, the next transformation is performed. opened and their transformation parameters have Image transformations can be performed by executing

Fig. 14. Original sample images with different graphic line colours.

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Fig. 15. Sample images from Fig. 14 after selecting the “Black-and-white positive” view. the full number of iterations first for one sample, then for saved and can be viewed (backwards and forwards) the other, or by performing transformations alternately, at any stage of the analysis by using the buttons once in one window and once in another. The second marked “<<” or “>>” in the “Transformation overview” approach is recommended as it gives an insight into box. Fig. 10 shows the main SCANGRAF interface the current shading visualization and allows for the with samples “A” and “B” opened for testing. Both ongoing assessment of its compatibility in samples. samples are graphometrically identical, but sample “B” All transformations (more precisely, sample images has a deliberately, clearly deformed shading system after subsequent transformations) are automatically in relation to sample “A”, for demonstration purposes.

Fig. 16. Sample images after three transformations (grey background partially removed).

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Fig. 17. Sample images after eight – sample “A” – and seven – sample B – transformations.

In reality, the discrepancies in the shading systems analysis after a different number of iterations (window between test samples are usually very subtle, A – 8, window B – 7) requires comment. Namely, it was unnoticeable to the naked eye, but SCANGRAF still due to the fact that the graphical line colour saturation reliably detects and visualizes them. varied significantly between both samples, which was For samples presented in figure 10, the default values clearly visible after the conversion (fig. 15). This is quite of the transformation parameters, i.e. 20 transformation a normal situation, as in practice the samples displaying iterations (repetitions), were adopted. Due to the the identical colour shading could hardly be expected. limited scope of this article, not all transformations can be presented. The figures below show the selected, Final remarks most characteristic images of signature samples Scangraphy can be used much more widely than after five (fig. 11), eight (fig. 12) and twelve (fig.13) described above. It was used, among others, in transformations. the BARWOSKAN and PROFILOSKAN programs Although 20 iterations were assumed when setting developed within the framework of the aforementioned the transformation parameters, already the twelfth development project No. DOBR-BIO4/038/13297/2013 transformation, shown in figure 13, very clearly entitled “Measuring tools to support to support visualized the shading inconsistencies, as indicated handwriting and signature analysis “. by red rectangles. Therefore, in this case it was not BARWOSKAN enables colorimetric analysis of inks necessary to continue the iterations. Upon obtaining the on the basis of the bitmap of a handwriting sample or sample images as presented in figure 13, the expert is its selected fragment, according to the RGB model. entitled to question the shading and pressuring identity. The results of the analysis in the form of records of the Figure 14 shows another pair of samples. number of all pixels in the sample image are presented Whenever the graphic lines have different colours, in graphs and histograms. This creates a quantitative it is recommended to convert them, i.e. replace the characteristic of the image colour content. The colour images with black-and-white equivalents, as analysis enables detection of differences in colour already mentioned. content between samples to be compared as well as After three iterations, the grey sample backgrounds parametrized evaluation of distribution and degree of begin to “brighten up” (fig. 16), but further transfor- the graphic line shading. mations are needed to assess the identity of the The PROFILOSKAN prophilometric program is used shading distribution. to analyze the pressure exerted by a writing instrument Figure 17 shows the sample images after the across a horizontal measurement line (one or more) analysis. No shading differences can be found and, determined by an expert (linear analysis) or at selected therefore, these samples can be considered as points (point analysis) in the samples compared. identical. The presentation of the final results of the

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An important novelty of both programs is that they writing expertise). Problemy Kryminalistyki (Issu- allow not only for a qualitative but also a quantitative es of Forensic Science), 294. assessment of the motor properties of writing, which 4. Harrison, W.R. (1958). Suspect Documents. Their include the shading distribution and the degree Scientific Examination. London: Sweet and Max- of pressure exerted by the writing instrument on well. the surface of the document. These programs 5. Hecker, M.R. (2000). Traktat über den Wissen- were discussed earlier (Goc, Łuszczuk, Łuszczuk, schaftlichkeitsanspruch der forensischen Schrift- Tomaszewski, 2016, pp. 13-27) and presented at vergleichung. Wroclaw: Kolonia. scientific conferences (Łuszczuk, Goc, Łuszczuk, 6. Kwiatkowska-Wójcikiewicz, V., Wójcikiewicz, J. 2013; Goc, Łuszczuk, Łuszczuk, Tomaszewski, 2014). (2010). O subiektywizmie biegłych uwag kilka Prototype programs have been submitted together (A few comments on the experts’ subjectivity). In: with the project implementation report to the NCBiR Z. Kegel (ed.), Aktualne tendencje w badaniach (National Centre for Research and Development) and dokumentów. Materiały XIII Wrocławskiego Sym- are awaiting implementation. pozjum Badań Pisma (Current trends in docu- The Forensic Science Institute of the Polish Forensic ment examination. Materials of the 13th Wroc- Association is carrying out conceptual and pilot law Symposium for Handwriting Examination) works, which result in further proposals of computer (pp. 319–328). Wroclaw: University of Wrocław, scangraphy-based applications, with wider possibilities Faculty of Law, Administration and Economics. than just handwriting analysis (e.g. INWERTOSKAN, 7. Łuszczuk, A., Goc, M., Łuszczuk, K. (2013). Aktu- BARWOMETR, PREZENTER programs). alne tendencje w ekspertyzie pismoznawczej, These applications allow to compare images, referat (niepublikowany) wygłoszony podczas drawings, forms, cheques, payment and credit cards, konferencji naukowej „Współczesna kryminalisty- identity cards, driving licenses, passports, diplomas ka – wyzwania i zagrożenia” w ramach VII Zjaz- and any other documents in cases when there is du Katedr Kryminalistyki w Wyższej Szkole Policji a suspicion that the colour pattern has been distorted (Current trends in handwriting expertise, lecture as a result of forgery or imperfect production processes. (unpublished) delivered during the scientific confe- Furthermore, the programs make it possible to invert and rence „Contemporary forensics – challenges and convert images, make them translucent and compare risks” as part of the 7th Congress of Forensic Chairs not only documents but also other objects and persons at the Police Academy in Szczytno). Szczytno, (monitoring records, traces on shells and projectiles, 9–11 September 2013. mechanoscopic and traseological traces, etc.). 8. Łuszczuk, A., Łuszczuk, K. (2012). Scangra- fia. Komputerowa, barwometryczna analiza pi- sma ręcznego (Scangraphy. Computer-based Sources of figures and table: authors colorimetric handwriting analysis). In: Z. Kegel, R. Cieśla (ed.), Znaczenie aktualnych metod Bibliography badań dokumentów w dowodzeniu sądowym. 1. Goc, M. (2016). Współczesny model ekspertyzy (Importance of current document examination pismoznawczej. Wykorzystanie nowych metod methods in judicial proceedings). Wroclaw: Legal i technik badawczych (A modern model of hand- and Economic Digital Library, University of Wroc- writing expertise. Use of new test methods and law, Faculty of Law, Administration and Econo- techniques). Warsaw–Szczecin: Volumina.pl – mics. Polskie Towarzystwo Kryminalistyczne (Polish 9. Moszczyński, J. (2011). Subiektywizm w bada- Forensic Association) 2nd edition. niach kryminalistycznych. Przyczyny i zakres sto- 2. Goc, M., Łuszczuk, A., Łuszczuk, K., Tomaszew- sowania subiektywnych ocen w wybranych meto- ski, T. (2014). Pomiarowe narzędzia wspomaga- dach identyfikacji człowieka. (Subjectivism in jące analizę pisma ręcznego i podpisów. Komu- forensic research. Reasons and scope of ap- nikat z realizacji projektu rozwojowego nr DOBR- plication of subjective evaluations in selected -BIO4/038/13297/2013, referat wygłoszony pod- methods of human identification). Olsztyn: Uni- czas VIII Zjazdu Katedr Kryminalistyki (Measuring versity of Warmia and Mazury Publishing House. tools to support handwriting and signature analysis. 10. Widła, T. (1982). Źródła błędów w opiniach pismo- Communication on the implementation of the deve- znawczych. (Sources of errors in handwriting lopment project No. DOBR-BIO4/038/13297/2013, opinions). Palestra, 11/12. lecture delivered during the 8th Congress of Forensic Chairs). Krakow 15–17 September 2014. 3. Goc, M., Łuszczuk, K., Łuszczuk, A., Tomaszew- Translation Rafał Wierzchosławski ski, T. (2016). Programy komputerowe jako narzę- dzie wspomagające ekspertyzę pisma ręcznego (Computer programs as a tool to support hand-

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