TR2022011957A1 - Mobile automatic fingerprint recognition system and method. - Google Patents

Abstract

The invention is related to the method and system that performs biometric recognition/verification using the finger images collected without contact with the new data acquisition method it contains. In particular, the invention collects finger images using a new contactless data acquisition method, converts the collected finger images into fingerprints using improvement methods, extracts characteristic features for biometric recognition/verification from the improved fingerprint image, uses a template consisting of the characteristic features of the fingerprint and other fingerprint images registered in the database. It is about the method and system that compares the templates of fingerprint samples, detects possible matching candidate(s) as a result of the comparison, and enables the fingerprint images collected to be used in biometric recognition/verification with the new data acquisition method it offers.

Description

DESCRIPTION MOBILE AUTOMATIC FINGERPRINT RECOGNITION SYSTEM AND METHOD Technical field to which the invention is related: The invention is related to a mobile automatic fingerprint recognition/verification method and system that enables the development and collection of finger images by contactless method, the improvement of the finger image to be converted into a fingerprint, the extraction of biometric characteristic features from the improved fingerprint, the use of this collected trace for identification or different purposes, and the management of all steps from a single center. The invention is particularly related to a fingerprint-based portable biometric recognition/verification method and system that incorporates a new contactless fingerprint acquisition method, develops and collects finger images with this method, improves the collected finger images, extracts characteristic features from the improved image, compares and matches these features with the features of fingerprint samples recorded in databases. State of the art: The most common procedures used to detect the characteristic pattern of a fingerprint require the finger to be placed or rolled onto a device plate such as a scanner, reader, sensor, etc., or the finger surface to be painted with a dye such as ink and pressed or rolled onto a surface such as a paper card, film, etc. The process of touching the finger surface painted with the dye onto a paper card and transferring the print on this card to the digital environment with the help of a device such as a scanner, etc. is called offline fingerprint acquisition or offline sensing. Today, most civil applications and law enforcement databases accept live scan digital images obtained by directly detecting the finger surface with an electronic fingerprint scanner. This method is called online sensing. In the online sensing process, ink or any colorant does not need to be applied to the finger surface. All that needs to be done is to bring the finger into contact with a data capture device such as a sensor, scanner, etc. to ensure that the print is transferred to the digital environment. In general, approaches used to detect and record the characteristic pattern on the finger surface work by using the contact-based data collection method. Contact means that the individual must press or roll their finger on a capture surface, and these actions requiring pressure cause deformation due to the deterioration of the elastic structure of the fingerprint. In order to prevent this deformation caused by pressure, new methods have been developed that can collect fingerprints without contact. In order for a fingerprint collected using any data acquisition method to be usable in biometric recognition/verification, the print must be converted to a suitable format for comparison and matching. This conversion process is referred to as image preprocessing. The image preprocessing process consists of a series of interventions in which many methods are parametrically adjusted according to the specifications of the image to be processed and more than one method is applied to the image in an appropriate order. The image processing process that should be applied to the fingerprint print is shaped according to which data acquisition method is used and the structure of the collected data. For this reason, when a new data acquisition method is proposed, the effective usability of the collected data in biometric recognition/verification should also be evaluated. The fingerprint, where the preprocessing process is completed, is now ready for the extraction of characteristic features that can distinguish the individual. These characteristic features are defined as detail points or Level-2 features. In addition, in some specific cases caused by external factors such as injury, disease, etc. or by some innate characteristics, characteristic data that cannot actually be classified as detail points but are distinctive are also observed in the fingerprint. These detail points and characteristics that are not classified as detail points but have distinguishing features are used together to perform biometric recognition/verification. For this reason, feature extraction is performed by using algorithms to extract these features from the developed and improved fingerprint template. After extracting features from the developed and improved fingerprint template, these features need to be compared with other sample templates that have a matching probability. If the system in which the fingerprint is used is designed only for verification, the sample registered in the system is compared with the newly collected sample. However, if the system is designed for recognition, the newly collected sample is compared with a certain group of samples registered in the system. If the similarity rate measured as a result of the comparison made in both recognition and verification exceeds the threshold level determined for the biometric recognition/verification system, these samples are labeled as templates with a probability of matching. In the state of the art, a biometric recognition/verification system in which fingerprint is used as a distinguishing element is designed to consist of five components that are capable of processing the data. These are data acquisition, feature extraction, matching, data storage and decision-making components. In order for the recognition/verification system to work properly and correctly over the specified five components, fingerprints are collected by taking into account the fulfillment of certain requirements related to distinctiveness within the framework of certain standards and specifications. Because the content of the collected biometric fingerprint and the amount of data it contains can directly affect the performance of the recognition/verification system, and for this reason, the data acquisition component is the most critical component. The quality of the biometric fingerprint data coming from the data acquisition component directly affects the performance of the other components. Since the data collected will vary depending on the technology used in the data acquisition component, the other components are designed in a way that can extract meaningful and usable information from this data. The discovery of fingerprint acquisition approaches and the completion of the development of these methods and their use with today's versions have been made possible by the collaboration of different disciplines and the adaptation of technological developments to existing methods. Academic studies and commercial software/hardware developments on fingerprint acquisition are currently being carried out to complete or improve the deficiencies of the developed techniques and methods, but many different problems arising from the application of the methods in both contact and non-contact methods currently used in fingerprint acquisition have not been overcome. In the contact fingerprint acquisition application, which is applied by placing the individual's finger on the image-detection plate or surface of a device such as a scanner or reader, or rolling it on this plate/surface, or pressing or rolling the finger on a paper surface after applying a coloring (dye) substance to the surface of the finger; (i) Data loss and/or incorrect data formation in the fingerprint image due to the pressure that occurs as a result of pressing the finger on the plate/surface in order to capture the ridge-valley prints on the finger surface, causing deformation in the elastic structure of the finger, (ii) although the same data acquisition process is used, parameters such as finger position/applied pressure/noise rate originating from the device, etc. are not exactly the same, so the number and type of final characteristic features in two different prints of the same fingerprint vary and/or the incorrect characteristics obtained from the noise also vary, (iii) deformations resulting from the finger surface being excessively dry/moist/wet, (iv) cuts/wounds, etc. on the finger surface. Problems are encountered due to (a) skin deformations caused by the previous individual's fingerprints mixing with the fingerprints of the next individual on the device used for data acquisition, (vi) noise originating from the data acquisition device, (vii) decreased performance and weakened durability of the data acquisition device during intensive use, and (viii) location problems such as inability to properly place the finger on the data acquisition device. In order to eliminate the problems existing in contact fingerprint acquisition methods, the contactless fingerprint acquisition method, which can collect fingerprints without any contact by using special data acquisition mechanisms and specialized image capture devices, is faced with the following issues: (i) problems arising from the data acquisition mechanisms used for contactless acquisition, (ii) problems arising from the environment in which data is collected during the contactless acquisition process, (iii) problems arising from the necessity of process steps that require too many guiding/assistant instructions for the data acquisition process, (iv) problems arising from the quality and adequacy of the collected fingerprint image, (v) problems arising from the necessity of using complex software and high-cost hardware during the data acquisition process, and (vi) complexity and application difficulties of the fingerprint image acquisition process in the methods used for contactless acquisition. The patent file numbered "TR201506503" and titled "Identity Access Device Including Contact, Contactless, Biometric, All Kinds of Electronic Payment Functions", which is in the known state of the art, has been examined. The summary section of the invention subject to the application is related to the Identity Access Device Including; upper cabinet, display frame, color touch screen, contactless reader, touch screen capacitive connector, touch screen light connector, SAM card slot, chip card reader area for the server, fingerprint and finger vein reader frame, USB port of palm (palm) vein reader, fingerprint and finger vein reader module, HDMl connection cable connector, external power supply, Ethernet interface, plastic cover of SAM card slot, lower cabinet, USB B type, mini USB, security point on the motherboard, security point on the motherboard, connection connector of fingerprint and finger vein reader device, motherboard bottom security cover, contactless antenna connector, PCB firewall, chip card reader area for the server, lock cover of SAM card slot, motherboard, keyboard illuminated protective area, functional password/PlN keys, LCD connector, button battery, micro HDMl, battery, SLM card slot 1, SLM card slot, charging module and It consists of SAM card slot parts." information is included. The patent file numbered "TR201513220" and titled "EFT-POS Featured Biometric Authentication Device", which is in the known state of the art, has been examined. The summary of the invention subject to the application includes the following information: "This invention is related to the Payment Device Capable of Biometric Identity Verification and consists of upper body, keyboard frame, screen protection frame, touch screen film, LCD screen, LCD screen holder, LCD screen connector, touch film connector, mainboard, smart card reader for the service recipient, smart card reader for the service provider, button battery, protective mesh wall, contactless antenna connector, tamper, tamper, lower body, SLM/SAM cover, fingerprint reader, USB connector, fingerprint reader connector, contactless antenna, protected area PCB security cover, contactless antenna connector, SLM reader, SAM reader, keyboard, keyboard holder, fingerprint reader protective frame, mini HDMl connector, battery, desktop charging station connector and hidden SAM parts." The patent file numbered "EP2645302" in the known state of the art has been examined. In the invention that is the subject of the application, a sensor that detects the movement of the living body part within the reader area and collects the recording data, a processor that organizes a certain number of data in a comparison range, a contactless biometric recognition system that selects the data that will work on the comparison range, will not overlap with each other and will have a maximum radius as recording data and its working method are mentioned. The patent file numbered "SE1950970" in the known state of the art has been examined. The invention that is the subject of the application is related to the fingerprint recognition system and method. With the finger touching the sensor screen, it creates and records fingerprint data thanks to an identifier that recognizes the fingerprint. In the known state of the art, it is seen that all the internal problems arising from the application of the methods in the existing fingerprint acquisition methods cannot be overcome. In particular, in the scanning, touching and swiping processes used in contact fingerprint collection methods, the print on the finger surface must be taken to the scanning screen, reader or paper and examined. At this stage, the amount and direction of pressure applied to create a fingerprint causes the template formed by the lines to fail to be obtained properly due to the deterioration in the elastic structure of the finger surface. In this context, losses and errors occur in the fingerprint data obtained. In contactless fingerprint collection methods, in addition to the problems arising from the data collection mechanisms used and the environment in which the trace is collected, the cost of the software and hardware used in contactless fingerprint collection and processing of the collected data, the complexity of the application instructions during the collection process also affect the quality, adequacy and collectability of the collected fingerprint data. Purpose of the invention: The most important purpose of the invention is to provide a portable recognition/verification system based on fingerprint biometrics, which can provide the same service as recognition/verification systems that work by using fingerprints collected using contact data acquisition methods, and which includes a new contactless fingerprint acquisition method that will eliminate the disadvantages of contact acquisition methods. The invention consists of a device developed to collect finger images from individuals with the contactless method it offers, methods and a system that extract, improve, compare and match fingerprints from the collected finger images. Another purpose of the invention is to provide a new non-contact fingerprint detection and development method as an alternative to contact methods in order not to be affected by any deformation problems caused by contact due to the nature of contact fingerprint acquisition methods (deformation caused by pressure, deformation caused by finger surface and skin problems, deformation caused by the use of the data acquisition device). Another purpose of the invention is to standardize the environmental conditions in which fingerprints are collected, which are the issues to be considered during the data collection phase in contactless fingerprint acquisition methods, to organize and design the equipment/device/hardware used and all kinds of data acquisition components to meet the requirements of the collected fingerprint image, to be able to collect fingerprints that have sufficient criteria for biometric recognition/verification regardless of environmental conditions, to control the factors affecting the data acquisition process and to present a new data acquisition mechanism developed to standardize all the steps performed. Another purpose of the invention is to provide a new low-cost, compact, portable and non-expertise contactless fingerprint data collection method as an alternative to the high-cost, non-portable and special installation data acquisition mechanisms of contactless data acquisition methods. One of the purposes of the invention is to provide a new data acquisition method that can be used practically in scenarios where only certain limbs of a cadaver or a corpse are present and data acquisition methods that require the state of being alive (requiring the use of pressure, temperature, etc.) cannot be used. Another purpose of the invention is to provide a biometric recognition/verification system that ensures that all components constituting the biometric system are coordinated with each other and standardizes the entire process, allowing the system to be managed from a single center and to be portable. In the state of the art, contact data acquisition approaches are preferred in biometric recognition/verification systems and biometric recognition/verification systems are always negatively affected by the disadvantages of using contact approaches. Due to the internal problems of contact acquisition methods, there is always some data loss or incorrect data collection in the collected fingerprint. Thanks to the invention, a method and device that does not contain the disadvantages of contact acquisition methods, can be used effectively in all biometric recognition/verification systems, and allows more and more accurate characteristic features to be extracted, is presented in which fingerprints are collected without contact. Another purpose of the invention is to control the data collection environment, which is an important element for contactless data acquisition approaches. Many academic studies on contactless approaches and prototypes developed for the implementation of these approaches use data acquisition mechanisms and imaging devices that are highly functional, costly, require professional use, have complex working mechanisms, are not portable, or use fingerprint data that is affected by environmental conditions and noisy, collected with simple (ordinary, classical) imaging devices without using a specialized mechanism for data collection. In the invention, the most optimal adjustment of many factors such as the environment in which the finger is viewed, the background, the type and intensity of the light source used, the resolution of the imaging device used, the depth of field, the focus, etc. provides the opportunity to obtain higher quality fingerprint images. In addition, the data acquisition (collection) device and method presented within the scope of the invention are much more cost-effective, easier to use compared to data acquisition mechanisms used in non-contact data acquisition approaches and can collect images in the same quality as already developed high-functionality/complex/high-cost designed mechanisms. In addition, the data acquisition mechanism and method in the invention are designed to obtain sufficient quality data even when used with imaging devices with ordinary features. Another purpose of the invention is to develop a device designed to work on live individuals and to provide data acquisition using pressure, temperature, etc. In cases where it is necessary to collect biometric data from a cadaver or a body part containing a finger surface, where fingerprint collection methods using factors are ineffective, it provides a new fingerprint detection and development method that can collect biometric characteristic data from body surfaces that do not show vitality. Thanks to its mobility feature, the invention eliminates the problem of operating biometric recognition/verification systems that require fixed installation and contain specialized data acquisition and transfer components/methods from certain centers/locations and performing the recognition/verification process only from these centers/locations. Complex process steps and special equipment requiring high functionality are not used in the development of both software and hardware components used in the design of the fingerprint-based biometric recognition/verification system presented within the scope of the invention. In particular, thanks to the use of a data acquisition mechanism that does not require a fixed infrastructure in the data acquisition component and the high quality of the collected data, a low-cost fingerprint data collection method and fingerprint-based biometric recognition/verification system have been developed without the need for complex development, improvement, feature extraction, comparison and matching approaches. In the invention, a more practical data collection model and an easy-to-use biometric recognition/verification system and method have been presented due to the fact that the fingerprint sample is recorded without the need for an assistant during the data acquisition process and that the stages such as data collection/storage/transmission are carried out very quickly and practically due to the use of a mobile device during the data acquisition process. Another purpose of the invention is to design each component of the invention in a way that it can be easily integrated into existing biometric-based recognition/verification infrastructures and to provide a new contactless data acquisition method that will enable the biometric fingerprint sample collected by the data acquisition component of the invention to work effectively in existing biometric recognition/verification systems. In the known state of the technique, the stages of collecting, developing, improving, extracting features, comparing and matching fingerprints in criminal-victim-crime relationships in criminal assessments are carried out with both technological equipment (computers, software tools, etc.) and field experts. In these stages, different field experts work to fulfill different tasks. In this context, one of the purposes of the invention is to provide a system that manages the steps of fingerprint collection, development, improvement, comparison and matching, which are carried out by different field experts and using different equipment for criminal evaluations, from a single center and contributes to the standardization of the working mechanism of all these steps. Explanation of the figures: FIGURE -1; The subject of the invention is the drawing showing the image of the device and data acquisition mechanism used to collect fingerprints. FIGURE -2; The subject of the invention is the drawing showing the working flow of the fingerprint recognition system. Reference numbers: 100. Mobile Device 110. Connection Device 120. Collection and Enhancement Module 121. Implementation of the contactless fingerprint acquisition process 122. Collection of candidate image 123. Evaluation of candidate image 124. Determination of ROI 125. Transmission of ROI image determined from candidate image to enhancement module via server 130. Enhancement Module 131. Adjustment of image contrast 132. Orientation estimation of ridge lines 133. Frequency estimation of ridge lines 134. Filtering 135. Binarization 136. Thinning 137. Evaluation of image 138. Completion of enhancement process 140. Feature Extraction Module 141. Detail point extraction 142. Removal of faulty characteristics 143. Evaluation of feature point map 144. Completion of characteristic detection process 150. Matching Module 151. Evaluation of characteristic features 152. Comparison of characteristic features with characteristic features of samples recorded in database 153. Calculation of matching scores 154. Detection of pairs with scores exceeding threshold value 155. Examination of similar pairs 156. Transmission of matched samples to mobile device 160. Control Module 161. Evaluation of candidate image according to data collection criteria 162. Decision on suitability of candidate images 163. Evaluation of image according to data enhancement criteria 164. Decision on adequacy of enhancement level 165. Comparison of feature extraction module of control module with feature point map defined in control module 166. Decision on the adequacy of the detail point map 167. Manual checking of similar pairs 200. Dark room box 210. Dark room box upper part 220. Dark room box lower part 230. Illumination Ring 240. Macro lens 250. Power supply Description of the invention: The invention is generally described as a collection and development module (120), improvement module (130), feature extraction module (140), matching module (150), control module connecting the developed method for developing fingerprints, collecting them without contact, improving them, transferring them to the central server, comparing them with fingerprint databases and transmitting the matching samples to the user as a result of the comparison. The apparatus (110) consists of a system consisting of a macro lens (240) used to better capture the details in the fingerprint, a dark room box upper part (210) and a dark room box lower part (220) designed to collect fingerprints, an illumination ring (230) used to illuminate the finger surface and a power source (250) in which the batteries used to power the LEDs in the dark room box are placed. All parts are made of a hard material such as bakelite that does not reflect light and their thickness is 5 mm. There is a space with a radius of 2 cm positioned in the middle of the dark room box upper part (210) and this ring-shaped space corresponds to the camera on the back surface of the mobile device (100). The macro lens (240) is installed in the space provided in the upper part (210) of the darkroom box in cases where the resolution of the lens of the camera of the mobile device (100) is insufficient, and the resolution is increased. A total of 6 yellow LEDs are positioned at equal distances from each other in the illumination ring (230), and the wavelength of the yellow LEDs used in the device is between 570-590 nm. After the ridge lines in the fingerprint are made more visible by means of these yellow LEDs located in the illumination ring (230), macro lenses (240) with +1, +4, +8, +10 close-up features are used in order to observe the details on the finger surface. These macro lenses (240) adjust the minimum focal length of the lens of the mobile device (100) used to image the fingerprint, allowing for closer approach to the fingerprint. Thus, the details of the fingerprint can be examined and more characteristic features can be captured. Rechargeable batteries in the power source (250) are used to operate the LEDs inside the device. The LEDs are turned on and off by means of the button in the power source (250). The imaging process of the fingerprint developed using the dark room box (200) is carried out by the mobile device (100), and the collected print is transmitted to the server by means of the mobile device (100) to be compared in the fingerprint database. As a result of the comparison, fingerprint samples that show similarity are transmitted to the user by means of the mobile device (100). For this reason, the mobile device (100) acts as a client in the client-server model. The server, with its collection and development module control module (160), provides the execution of the fingerprint recognition/verification system and the methods in the system. The connection apparatus (110) is used to connect the mobile device (100) to the darkroom box (200). The darkroom box (200) consists of the darkroom box upper part (210) and the darkroom box lower part (220) used to provide suitable environmental conditions and to better capture the details of the finger image, and includes the illumination ring (230), macro lens (240) and power supply (250). The illumination ring (230) is used to provide sufficient illumination and to obtain the contrast value during imaging of the finger surface. The macro lens (240) is used to collect the image of the developed fingerprint with higher resolution. The power source (250) provides the energy required for the operation of the illumination ring (230). There are conditions that must be met during the use of the device that collects and develops the fingerprint in a contactless manner and the method included in the enhancement, feature extraction and matching processes. The fingerprint imaging device is designed to view the fingerprint from above. For this reason, the finger surface and the device are positioned at a 90-degree angle. The method and system responsible for fingerprint enhancement, matching, feature extraction and control of all these operate on a client-server architecture basis. The mobile device (100) provides the client role and can be connected to the server via wired or wireless. For this reason, if it is desired to obtain instant results in the place where the fingerprint is collected, the mobile device (100) must have the necessary communication infrastructure to access the server. The designed fingerprint image acquisition device can perform its duty in conditions such as temperature, humidity, pressure etc. where the functions of the mobile device (100) and the LED lamps and 9-volt battery in the power source (250) can work properly. The invention is a system that performs biometric recognition/verification using fingerprints collected with a contactless method operating with a client-server architecture. There is a contactless data acquisition device specially developed to collect fingerprint images in this system. The invention consists of a device (Figure-1) consisting of interconnectable parts and developed for contactless fingerprint collection and a method using five system modules developed for biometric recognition/verification. The fingerprint recognition/verification method, which is the subject of the invention, has a collection and development module and a control module (160), and the system formed by these modules is run over a server. This method and system generally; - Collecting the candidate fingerprint image (122) with the mobile device (100) and the data acquisition device located in the darkroom box (200), - Transmitting the images collected by the mobile device (100) to the server, - Transmitting the collected candidate image to the control module (160) for the collection and development module (120) to evaluate it (123), The control module (160) evaluates the candidate image according to the data collection criteria transmitted by the collection and development module (120) and defined in the control module (160) (161), The control module (160) makes a decision on the suitability of the collected candidate images (162), If the candidate image is suitable, the control module (160) determines the ROI (124) (Region of Interest - The relevant region to be used in feature extraction) If the candidate image is not suitable, the control module (160) sends a command to the collection and development module (120) to start the data acquisition mechanism connected to the mobile device from the beginning and to perform the contactless fingerprint acquisition process (121). With the positive feedback received from the control module (160), the collection and development module (120) determines the ROI from the fingerprint image (124). The determined ROI image is transmitted to the enhancement module (130) via the server (125). The contrast value in the image transmitted from the collection and development module (120) to the enhancement module (130) is adjusted by the enhancement module (130) (131), and then the orientation estimation (132) and frequency estimation (133) of the ridge lines in the image are made. The filtering (134), binarization (135) and thinning (136) processes are applied to the fingerprint image whose contrast has been adjusted by the enhancement module (130), the enhancement module (130) transmits the image to the control module (160) for the evaluation of the fingerprint image that has been improved and made ready for feature extraction (137), If the image meets the enhancement criteria and a decision is made on the adequacy of the enhancement level (164) as a result of the evaluation made in the control module (160), the control module (160) transmits a command to the enhancement module (130) to continue the process, If the image does not meet the enhancement criteria, the control module (160) transmits a command to the collection and enhancement module (120) to restart the data acquisition mechanism connected to the mobile device and perform the contactless fingerprint acquisition process (121), The enhancement module (130) receiving positive feedback from the module (160) completes the enhancement process (138) and transmits the image to the feature extraction module (140). The feature extraction module (140) extracts the detail points in the image coming from the enhancement module (130) (141) and then removes the faulty characteristics in these extracted detail points (142). The feature extraction module (140) transmits the detail point map obtained from the fingerprint image to the control module (160) for evaluation (143). The control module (160) evaluates the detail point map transmitted by the feature extraction module (140) by looking at the characteristic feature extraction criteria defined in the control module (160) (165). As a result of the evaluation, if it is decided that the feature point map is sufficient (166), the control module (160) sends a command to the feature extraction module (140) to continue the process. If the characteristics in the feature point map are incorrect/insufficient, the control module (160) sends a command to the collection and development module (120) to start the data acquisition mechanism connected to the mobile device from the beginning and to perform the contactless fingerprint acquisition process (121). As a result of the evaluation from the control module (160), the feature extraction module (140) completes the characteristic detection process (144) and transmits the image to the matching module (150). The matching module (150) evaluates the characteristic features transmitted from the feature extraction module (140) (151) and then compares these characteristic features with the characteristic features of the samples recorded in the database. - Comparison (152), As a result of the comparison, calculating the matching scores (153) and detecting the pairs with scores exceeding the threshold value (154), Transmitting the fingerprint pairs (155) exceeding the threshold value to the control module (160) so that the matching module (150) can perform a more detailed similarity analysis, - After the control module (160) completes the process of manually checking the similar pairs (167), it transmits the results it obtains to the matching module (150), - Transmitting the matching samples to the mobile device by the matching module (150) in line with the feedback it receives from the control module (160), the process steps include. The details of the modules included in the method operating on the server to which the fingerprint image obtained using the data acquisition mechanism located in the mobile device (100) and the dark room box (200) is transmitted are as follows. The collection and development module (120) has three tasks and these tasks are defined as developing the finger image by providing appropriate environmental conditions, digitizing and recording the developed image, and finally sending the collected image to the central servers. The collection and development module (120) consists of the mobile device (100) used to capture, record and transmit the finger image to the server, the illumination ring (230) used to make the characteristic features on the finger surface and the details in the ridge-valley pattern more distinct, the macro lens (240) used to assist the camera of the mobile device (100) in recording the ridge-valley pattern on the finger surface and the external characteristics outside this pattern in more detail and to detect more specific details, and the dark room box (200). There is a mechanism designed to fix the finger position and angle in the dark room box (200) specially designed to both regulate the data acquisition environment conditions and guide the individual during the fingerprint collection phase. With this mechanism, the individual is guided and positioning errors that may occur during the data acquisition phase are prevented. The device, which consists of the dark room box (200) and the data acquisition mechanism, operates in an integrated manner with the mobile device (100). This device has an illumination ring (230), a macro lens (240) and a curved section that serves as a guide for positioning the finger image. The finger image is recorded using the mobile device (100) and the mechanism in the dark room box (200) integrated with the mobile device (100). The image is then sent to the control module (160) to evaluate whether it meets the desired criteria. If the image complies with the specified standards, the next step is passed; if not, the finger imaging process is repeated. If the collected image is deemed appropriate by the control module (160), the relevant region is cropped based on the seed point in the image. Afterwards, the cropped image is transmitted to the server and transferred to the enhancement module (130). The enhancement module (130) has been developed to convert the finger image collected with the collection and enhancement module (120) into a format that a biometric system can use. The tasks of this module are to increase image contrast, reduce noise, highlight ridge (line) lines, merge broken line lines, fill gaps in the ridge-valley template, increase the interpretability of the finger image, prepare the image for feature extraction and reduce the data size. The enhancement module (130) consists of the steps of the methods used for segmentation, normalization and filtering. The fingerprint image is expressed with two different regions, the background and the background. The foreground is defined as the region containing the fingerprint line lines and important characteristics, and the background is defined as the region outside the boundaries of the image. Segmentation is a step applied to distinguish the foreground region from the background region. This step is applied to reduce the data size, shorten the image processing process and perform accurate feature extraction. Thanks to the dark room box (200) designed so that the data acquisition stage is not affected by the environmental conditions, there is no problem such as separating the finger image from complex backgrounds. In this separation process, segmentation is easily performed by using the pixel density variable determined based on the background with the adaptive threshold method. In the images obtained from the collection and enhancement module (120), problems such as low contrast, lack/discontinuity in the ridge-valley template and noise resulting from the data acquisition stage are eliminated in the normalization stage. In this stage, the image is improved by changing the pixel values in the image without damaging the structure of the ridge lines in the fingerprint. The normalization of the collected finger images was performed using the contrast limited adaptive histogram equalization method. In this way, the contrast value between the peaks and valleys in the ridge-valley pattern was increased as much as possible and the brightness level of the image was improved for better observation of this pattern. In other words, a certain level of clarity was provided to the image. The finger images obtained from the collection and enhancement module (120) also contain deformations such as discontinuities/deficiencies, pores and/or defects caused by noise, etc. in the ridge-valley pattern that cannot be corrected by enhancing the pixels. The spatial domain filtering method was used for the restoration of these deformations. In the enhancement module (130), the contrast values of the image are adjusted in order to make the ridge-valley pattern on the finger surface more distinct. Then, the orientations and frequencies of the line lines that become apparent with the contrast adjustment are calculated to be used in the filtering step later. In order to eliminate the breaks/gaps in the line lines forming the fingerprint, the deficiencies caused by not capturing sufficient tone differences in the ridge-valley pattern, etc., the orientations and frequencies (frequencies) of the line lines are used to eliminate these defects with spatial domain filters. Then, the ridge lines are subjected to the thinning and binarization process to obtain the skeleton image of the ridge-valley pattern. In order to measure the usability of the finger image whose enhancement is completed in a biometric system, the enhanced image is transmitted to the control module (160). If the control module (160) decides that the finger image is sufficiently enhanced, it transmits this decision to the enhancement module (130). Finally, the enhancement module (130) transmits the enhanced image to the feature extraction module (140). The finger image collected with the mobile device (100) is now converted into a fingerprint after the data enhancement step. In this step, the necessary distinguishing elements from the fingerprint for the biometric system to perform recognition/verification need to be determined. The feature extraction module (140) has been developed to detect the detail points to be used to identify the individual in the enhanced fingerprint. The task of this module is to convert the enhanced and enhanced fingerprint into a suitable format for feature extraction (position and zoom adjustments), extract the characteristic features to be used for the biometric recognition/verification process, detect the location/position of these characteristics and determine their type, and create the map of the detail points in the ridge-valley pattern. The feature extraction module (140) is designed to detect biometric distinguishing elements from the fingerprint collected, developed and improved with the data collection mechanism. The operation of the feature extraction module (140) consists of sequential stages. A feature point-based comparison is performed in the biometric recognition/verification process. Although filtering processes are performed to prevent incorrect characteristics from being extracted at the end parts of the fingerprint, the end point of the print can be labeled as a feature point. The feature extraction module (140) checks whether such incorrect characteristics exist and if any, they are cleaned. Then, other feature points are examined. In order to evaluate whether there are errors resulting from the failure of the image collection and development and/or enhancement process at these points, the fingerprint image with the marked detail points is transmitted to the control module (160). If the control module (160) decides that the detail points are correct and sufficient, it transmits this decision to the feature extraction module (140). Finally, the detail points verified by the control module (160) are directed to the matching module (150) by the feature extraction module (140). The tasks of the matching module (150), where the data from the feature extraction module (140) arrives in the fourth stage, are; to compare the collected fingerprints with the registered samples in the database, to calculate the similarity scores in the compared samples, to list the pairs with similar features and to transmit them to the control module (160), and finally to transmit the samples that are deemed to match by the control module (160) to the client mobile device (100). The components of the matching module (150) are the matching methods used to compare the collected fingerprints and to calculate the similarity scores, and the fingerprint database where the comparison will be made. This database is where the samples to be compared are recorded. The detail point map coming from the feature extraction module (140) and the detail point maps of the registered samples in the database are compared with the matching methods. The distinguishing characteristics of a fingerprint and the positions of these characteristics relative to each other form a template. This template is actually a detail point map that summarizes the fingerprint. When comparing two fingerprints, the matching rates of these maps are observed. The characteristics found in two samples of a finger are never the same due to the nature of the data acquisition process. For this reason, the system is expected to be tolerant up to a certain level when matching the detail point map. This tolerance is defined as the threshold value of the matching module (150). The operation of the matching module (150) developed by taking these concepts into consideration is to calculate a matching score between the pairs compared as a result of the comparison made with the detail point templates of other recorded samples in the database and each sample in base 1, by comparing the detail points marked by the feature extraction module (140) in order. This score is related to the number of similar detail points (number of matching features) and the similarity captured in the maps formed by these detail points (template similarity). The increase in the similarity relationship means that the probability of two samples belonging to the same individual increases. Pairs with scores exceeding the similarity threshold determined for the invention are listed. In some cases, although fingerprint pairs show high similarity, the parts that do not show similarity are sufficient to separate the two prints. In case this or similar scenarios occur, similar pairs are re-evaluated by the control module (160). The similar pairs are transmitted to the mobile device (100) by the matching module (150) after the verification of the control module (160). The last module, the control module (160), has been developed to eliminate the disadvantages of fingerprint recognition/verification systems. This module consists of methods developed to control the outputs obtained from the collection and development module (120), enhancement module (130), feature extraction module (140) and matching module (150) and to produce a definitive result regarding the successful or unsuccessful completion of the process steps performed in these modules. The control module (160), designed to compare the minimum expected result from each module with the result obtained from the module, consists of a method designed using the criteria determined to evaluate the results obtained from the image collection and enhancement (120), enhancement (130), feature extraction (140) and matching (150) modules. These criteria were specifically selected to be able to evaluate the performance of the modules and the control module (160) was enabled to make decisions by using the combination of these criteria. The threshold values determined for these criteria were calculated by taking the average of the results obtained as a result of the tests performed using data sets with different characteristics. The control module (160) compares the output obtained from each module connected to the system with the evaluation criteria previously determined and defined in the control module (160), and decides which module needs to work again, and if a module successfully completes its task, it decides that the output obtained from that module is suitable to be transmitted to the next module, thus ensuring that the processed fingerprint data progresses in the system. The control module (160) has evaluation criteria for evaluating the results obtained from other modules. While the control module (160) determines whether the finger image obtained from the collection and enhancement module (120) is suitable to be inserted into the enhancement module (130); The method includes evaluation criteria established using predetermined threshold values for the parameters of the quality, resolution, pixel density, sharpness/blur, size of the image and location/position of the finger surface during the imaging process of the collected finger image. The control module (160) determines whether the finger image output from the enhancement module (130) is suitable for input into the feature extraction module (140), while the method includes evaluation criteria established using predetermined threshold values for the frequency and orientation of the ridge lines in the ridge-valley pattern. In addition, it performs a manual evaluation of whether there is an obvious problem in the ridge-valley pattern. The control module (160) determines whether the fingerprint extracted from the feature extraction module (140) is suitable for insertion into the matching module (150), using a method that includes evaluation criteria created using the detected characteristic amount (detail point amount) and predetermined threshold values for the distinctiveness of the detected characteristics. The matching module (150) sends the fingerprints that are similar to the collected fingerprint from the samples recorded in the database to the control module (160). In the control module (160), the method is used which includes the evaluation criteria created by using the similarity rate of the fingerprint pair/pairs that show similarity as a result of the comparison of the collected fingerprints with the fingerprints in the database, the number of registered fingerprints that show similarity with the collected fingerprint (total number of samples with a possible match probability) and the predetermined threshold values for the distinctiveness of the matching characteristics. The threshold values of the evaluation criteria in the control module (160) are determined as a result of the measurements made on the collected fingerprints with the collection and development module (120). The control module (160) is the module where all critical decisions are made while the method and system are operating. The output produced by each module is re-evaluated in the control module (160). In order to detect all undesirable situations in advance, evaluations are made in line with the criteria in the control module (160). While the relationships between the modules are unidirectional, the relationships between all modules and the control module (160) are bidirectional. The control module (160) has tasks for each module. The control module (160) checks the suitability of the candidate images coming from the collection and enhancement module (120). The candidate images are evaluated by looking at the criteria (given above) such as resolution, blur, positioning, etc. in the control module (160). If there is no obvious error that can be observed in the collected finger image in this evaluation, the control module (160) commands the collection and enhancement module (120) to transmit the collected image to the enhancement module (130). If the finger image is not collected appropriately, the control module (160) decides that the collection and enhancement module (120) should work again. The candidate image transmitted to the enhancement module (130) by the control module (160) is enhanced in both pixel size and contextual filtering size. The enhanced finger image is evaluated a second time in the control module (160). Here, the control module (160) evaluates the sections that cannot be enhanced in particular and investigates the reasons why these sections cannot be enhanced (deformations on the finger surface, illumination intensity, used lens resolution, finger size/position). In addition, the control module (160), independently of the result in the collection and enhancement module (120), checks whether the situation is caused by the special condition of the imaged finger, by changing the parametric values of the techniques and methods used in the enhancement module (130) and checking whether the performance increase is observed by increasing/decreasing the sensitivity values of the working functions. After these checks, if the control module (160) concludes that the result obtained from the enhancement module (130) is not sufficient, it decides to run the collection and enhancement module (120) again and collect the finger image again. If the control module (160) concludes that the enhancement is sufficient, the enhanced fingerprint image is transmitted to the feature extraction module (140). The detail points detected by the feature extraction module (140) are also evaluated by the control module (160). The extracted features may be erroneous as a result of an unsuccessful improvement process. In such and similar possible situations, the control module (160) checks whether the distinguishing points are Level-2 characteristics and other distinguishing elements by observing. If the control module (160) detects an error in the characteristics included in the detail point map, it sends a decision to the collection and enhancement module (120) to collect the finger image again. If no such problem is observed, the decision module (160) decides that the detail point map presented by the feature extraction module (140) is suitable to be transmitted to the matching module (150). The final task of the control module (160) is to compare the similarity of the fingerprint samples in the database transmitted by the matching module (150) and exceeding the matching score with the collected sample. The overlapping and non-overlapping parts from the detail point maps of both the collected image and the image in the database are manually examined. After this examination, the list of similar samples is finally transmitted to the matching module (150). As a result, within the scope of the invention; a new data acquisition device and method that can collect fingerprints with contactless approaches using a mobile device (100) has been developed by resolving the problems encountered in the previous technique. In addition, within the scope of the invention, a portable biometric recognition/verification system has been designed that will standardize the stages of fingerprint development, collection, improvement, feature extraction, comparison and matching, and a device and method that allows a fingerprint usable in biometric recognition/verification systems to be collected with a mobile device (100) has been developed. In the stages of developing, collecting, improving, feature extraction and matching of the contactless collected fingerprint, new methods have been developed using the criteria specified above in the control module (160) designed to evaluate the results obtained from these stages and to decide which step to repeat and/or which stage to return to as a result of this evaluation. TR TR TR TR TR