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201Fingerprint Based Access Control, System(Kerber- 1)) , .

Bogdan Rusyn, Volodymyr Ostap, Oleh Ostap,Oleh K apshiy, Viroslav Kapshiy, Volodymy r YelchevAbsrrocr - Al l stages of process of fingerprintidentificatio n system's de velop ment are considered. Such partsof the system as: comp ression, preproce ssing, postprocessing,feature extraction. feature comparison .and device creation aredescribed.K w o r d s - biometric identification system, fingerprint,image proceying, recognition, compression.

.' , LI NTRODUCTI ON.Methods and hardware for information protection arevery important in information technology age. The most ofknown guard devices are based on various kinds ofmechanical or electronic keys (for example: passwords, keys,smart-cards, electrical-keys etc.). They have one important

disadvantage, which can easily destroy protection. It ispossible of voluntary or involuntary h anding of key from legalperson to impostor. Such disadvantage has initiated biometricidentification systems development. These systems use somebiometric information read from human body instead of anykeys. So,. iris, fingerprint, face, hand, ear, etc. are used asbiometric keys. The most sp ecialists say that iris identificationsystems are most reliable, but they are complicated andexpensive (the price is about 5000%). Fingerprintidentification systems are used frequently, because they arecheaper (the price is about 100-IOOOS) and theylguamnteesufticientiy low false accept rate (FAR ) - about 10".Many of the worldwide companies propose fingerprintidentification systems, but research in the field of biometricsare not stopped. The competition between producers makesnecessity of future research. The customers want to bu ycheapest and most reliable systems, so producers have tosatisfy their needs.Ukrainian biometric systems' market is empty anduncultivated, because quality of domestically produceddevices is not very good. Foreign devices are also absent onUkrainian market, because of high p rice.Above men tioned fac ts, wer e taken into account beforebeginning of developing fingerprint recognition methods andalgorithms for own biometrics identification system. " .Our research field includes next stages:1. Fingers images compression methods development;

Bogdan Rusyn, Volodymyr Ostap, Oleh Ostap, Oleh Kapshiy- Karpenko Physico-Mechanical nstitute, Naukova str., 5,Lviv, 79601, UKRAINE, E-mail: russn:~ipni.lvir.iia,vt,L;i?r:i~ni. lviv.i14 l;l~rhi~;i~,iDni,luiv.oaViroslav Kapshiy - Lviv Radio Engineering Research Ins tipte ,Naukova str.. 7. Lviv. 79601. UKRAINE. ,Volodymyr Yelchev - SofiServe, Inc. - Ukraine Office,V. Velykoho St., 52, Lviv, 79053,UKRAINE,E-mail ~vrlcllcv,i~~~,Rscrvzcl,ln.roni

2. Development of image processing,, image ,ana lyzi ng,a ndfeature extraction methods; '3. Recognition m ethods 'development; ,4: Tuning algorithms' parameters' for given biosensor;5 . Hardware implementahon of the system; , '6. Software development, system programming.

8 .11. COMPRESSION.Developed compression algorithm is based on waveletdecomposition and is adapted io fingerprint images. Thepreservation of fingerprint ridges was the main goal, becausemost of needed information is concentrated in these structuralelements. The raw (fig.l.a), compressed (fig.1.b) anddifference images (fig.1 c) show that most of compressiondistortions are located in the high-frequency spectral band andare not important. The algorithm allows 8-times compressionwith PSNR =38dB, spending time, about 0,5 second (IntelPentiumlII-600MHz personal computer).

. . . ... .- . . ..

Fig.1. Input (a), compressed (b)and amplified difference image (c).111. PROCESSING AN D FEATURES EXTRACTION.Primary aim s of this stage are following:

- elimination or reducing fingerprint ridge patterndistortions app eared during capturing;-- features vector creation.

features extraction from given image;

. . .Fig.2. Processing results:a) -preprocessed grayscale image; b)- celeton; c)- esult imagewith minutiae.

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202In fig.2.a resu lts of preprocessing of the raw image(fig. 1.a) is shown. -This stage improves results o f skeletization(fig.2.h). The skeleton is needed for features extraction(fig.2.c). Features vector includes position, orientation andinterposition of minutiae's. P rocessin g time is about 100milliseconds for image's siz e 400x300 pixels.

IV. FEATURESECTORS COMPARISON.The aim of this stage is making decision aboutfingerprints .identity. Features vector is used for graphcreation. Graph nodes correspond to minutiae's (fig.2.c),graph branches - interpositions of minutiae's. Also, additionaldescription of fingerprint pattem around each minutia is usedfor achieving higher recognition speed. So, recognitionalgorithm compares input image's graph and images' graphsfrom data base (fie.31.

a) . b)Fig.3. Comparison oft wo fingerprint patterns:a) - caled, shifted and rotated input image; 'b)- etalon image. ,Output result of the comparison is the maximalmatching sc ore. between input and databa se pattern. Ifmatching score is higher than some identification thresholdthan decision about identity is accepted.Developed recognition algorithm and features vectorsare invariant to images scale - = *20%, rotation ~ *180 shift

- necessary images' common area 525%. Intellect elements,used in the algorithm, decrease negative effect of elasticdistortions and increase identification quality.As a result, our algorithms are characterized by: falseaccept rate =IOd, and false refusal rate =IO4, that allows OUTalgorithms to compete with the hest w orldwide systems [3].

V. SYSTEM TEACHING'ANDUNING.A lot of sensors' types have been developed. There aresemiconductor, capacitance, optical, ultrasonic, thermal typesamong them. It is not easy way to develop universalalgorithms that can work with all types of sensors, becauseeach type needs fitting many algorithms' Carameters forreliable work. So, algorithm, and program for automatic

system tuning based on ' client-server technology (withdistributed calculation process) were developed. Thealgorithm is .' based on iterative tuning of fingerprintrecognition systems' parameters with minimization of FA Rand FRR with a help of Levenberg-Macvardt's method [I].System training was carried ou t using training database thatincludes 20000 fingerprints images. Cluster based programwhich distributes calculation on 'many personal computersallows time of training to he significantly decreased.

. Recognition and training algorithms mentioned abovewere implemented and approved in biometric systems ofcompany "Testech Inc" [2] (fig.4). Among them:

a) b) C)Fig.4. Existent fingerprin t dentification systems.1 . Sensor for personal computer. It is used for accesscontrol and information protection on the PC (fig. 4a).2. Identification m odule that, includes fingerprint sens orand control hoard with microprocessor HITACHI (used as acalculation unit). This type of devices is used for creatinganother fingerprint based access control systems (fig. 4b).3. Sngerprint identification systemfor controlling rooms' access. It can heextended to many places using system'spossibility towork i n networks (fig.4~).But these devices' production out of

Ukraine has an essential disadvantage - ahigh price. Due to this condition, thesedevices have not widespread in Ukraine. fig.!. "Cerber-I"VI. DEVICE REATION.Taking into account mentioned circumstance, a newaccess control device "Cerher" was developed. Form of itsmain unit is presented in the fig3 and its block diagram ispresented in the fig.6.

G u a r d e d s p a c e

, , . , ,. , . ,b%- - - - - - - - .*u!eFig.?.bd?Fig.6. Flow-chartof "Cerber".

Developing the own system allows prime cost of theThere are next advan tages of the developed device:

I , Low price;2. Autonomous work (device does not need a PC for setup);3. Adaptation to Ukrainian market (emergency powerIt gives a right to tall about great potential of this devices'

device to he decreased in comparison w ith foreign analogs.

supply, open d oor sensor, breaking signalization, etc)productionand actuality of the research&development.

REFERENCES[I ] non. pea. B.r.ropcKoro, He h e r i x o e oyeausaxue121 http://ww.testech.com.kr[3] http:/mias.csr.unibd.i t

napcwempm, Moc~sa:3nwse, 919..

TCSET'2004,. February 24-2 8, 20 04, Lviv-Slavsko, Ukraine

http://ww.testech.com.kr/http:///mias.csr.unibd.ithttp:///mias.csr.unibd.ithttp://ww.testech.com.kr/