Research and Application of Fingerprint Recognition Based on MATLAB

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1 Send Orders for Reprnts to The Open Automaton and Control Systems Journal, 205, 7, Open Access Research and Applcaton of Fngerprnt Recognton Based on MATLAB Nng Lu* Department of Computer Scence and Applcaton, Zhengzhou Insttute of Aeronautcal Industry Management, Henan Zhengzhou 45005, Chna Abstract: Wth the development of bometrc technology, fngerprnt recognton technology contnues to be wdely used n practce due to ts unqueness and relablty, It trends to replace other tradtonal methods. By usng Matlab as a smulaton platform and makng the best use of ts tools, such as powerful graphcs and multple and practcal toolbox, etc. The paper makes a seres of mage processng of the llustraton of fngerprnt recognton system. Fnally, we extract the fngerprnt mage feature through the experment. Keywords: Fngerprnt mage, MATLAB, mage processng.. INTRODUCTION [-3] Under the background of nformaton age, electronc nformaton has a rapd development. And the mprovement of the dgtal and automatc dentfcaton s also reflected n personal dentfcaton. The network s wdely used at present. There are mportant nformaton securty problems, especally, nclude the nformaton securty of personal dentty. But our country's varous dentty management n the area of electronc and dgtal applcaton s not very perfect. There are a lot of loopholes n recognton. And these loopholes can cause a lot of socal problems. However, the method of fngerprnt dentfcaton can avod the trouble. Therefore, fngerprnt dentfcaton technology s wdely used n the feld of bologcal recognton technology and made a key research at present. The basc schematc dagram of fngerprnt dentfcaton s shown n (Fg. ). 2. THE PROCESS OF FINGERPRINT IDENTIFICA- TION [4-8] The man steps of fngerprnt dentfcaton technology s shown as the followng. () Collect the fngerprnt mage; () Read the fngerprnt mage; () The preprocessng of fngerprnt mage; (v) To extract the feature ponts; (v) Save the data and the feature matchng. After the extracton of fngerprnt feature ponts, we wll make the fngerprnt feature pont matchng. The fnal results of fngerprnt dentfcaton s matched through the results. The entre mage processng process s shown n (Fg. 2). Fngerprnt Acquston The Preprocessng of Fngerprnt Image The Output Shows THE Extracton of Feature Pont THE Matchng of Feature ponts Fg. (). The schematc dagram of fngerprnt dentfcaton. The mage segmentaton The mage enhancement The mage bnarzaton The preprocessng of fngerprnt mage The mage thnnng The e xtracton mage feature Fg. (2). The flow chart of fngerprnt mage processng twodmensonal eght shape model. 2.. The MATLAB Applcaton In Image Processng MATLAB has read and dsplay functon of the mage, and the followng s a way to read and dsplay grayscale /5 205 Bentham Open

2 08 The Open Automaton and Control Systems Journal, 205, Volume 7 Nng Lu mages, that s, [X,Cmap]=mread, %( d:\fngerprnt\casi- A_DBI\_.bmp); %Read bmp format fle Cmap; %Observe color map matrx Imagesc(X); %Dsplay grayscale mages Where, X s a matrx of the gray value of a stored fngerprnt mage. Gray value mage s correspondng to the value of each element wthn the matrx. To make the mage dgtzed, and the mage s processed ndrectly through the matrx values. We wll observe the result untl the mage s output by MATLAB The Fngerprnt Image Segmentaton Fngerprnt mage segmentaton, n the front of the fngerprnt mage preprocessng, t s one of mportant and dffculty steps n the process of fngerprnt mage processng. The purpose of mage segmentaton s to dvde the mage nto several has certan sgnfcance of sub area or a certan purpose. We can accordng to each pxel of mage segmentaton, stll can use the mage nformaton segmentaton wthn the specfed range to complete the mage segmentaton. By fngerprnt extracton of the orgnal mage s shown n (Fg. 3). Fg. (3). The orgnal fngerprnt mage. The program of readng mage s that, sample=mread ( zhwen.bmp ), %read mage fgure, mshow(sample) The formula of the fngerprnt mage processng s gven as follows. M G( = # M " % v0 ( I( % M ), I( > M v v0 ( I( % M ), I( < M v Eq. () Where, M 0 and M are the desred mean value, mean value of fngerprnt mage respectvely. Whle v 0 and v are the desred varance, varance of fngerprnt mage respectvely The Fngerprnt Image Enhancement After the fngerprnt mage segmentaton, we need to make a flter processng n order to elmnate the nterference of nose on the mage processng. Fnally, t wll further mprove the effcency of fngerprnt mage recognton. The fngerprnt mage enhancement s usually used to process the mage whch has a low qualty and obscure effect. Therefore t wll let the structure and texture of fngerprnt more clear and elmnate some false feature nformaton. Fnally, t wll retan some key feature nformaton for the fngerprnt recognton. Then ths can make the fngerprnt dentfcaton more accurate and relable. In ths paper, we combne the medan flterng wth the hgh pass flterng technology to process the fngerprnt mage. Where, medan flterng has some mportant feature as follows. () One dmensonal medan flter can mantan the nvarance of some certan types of nput sgnals, such as the seres of monotone ncreasng or reducng or the step seres. The output sgnal of medan flterng s constant. () The denosng performance of medan flter. When the mage has random nterference and pulse nterference, medan flter can reduce the nose nterference.ths s the superorty on the denosng performance of medan flter. M s used to express the medan of f ( whch s one-dmensonal or two-dmensonal. Set C as a constant. Then the followng equaton s true. () { f ( { C f ( = C Mf ( M { C + f ( = C M{ f ( M + { f ( + g( M{ f ( M{ f ( M + Eq. (2) Eq. (3) Eq. (4) Usng 3 3 medan flterng template to process the fngerprnt mage (Fg. 3), then we can get the (Fg. 4) below. Fg. (4). The fngerprnt mage after medan flterng. The program of readng mage s that, smooth=medflt2(sample, [3,3]) fgure, mshow(smooth) Hgh pass flterng s usually carred out after the medan flterng. Hgh pass flterng can enhance the hgh frequency component of mage wthout changng the low frequency components, whle the general means wll weaken the low

3 Research and Applcaton of Fngerprnt Recognton Based on Matlab The Open Automaton and Control Systems Journal, 205, Volume 7 09 frequency components when the hgh frequency component of mage s enhancement. Hgh pass flter can enhance the edge of fngerprnt mage. It s the bass for the realzaton of fngerprnt mage edge detecton. The smooth nformaton n fngerprnt mage s substantally suppressed by hgh pass flter. And t can make the sharpenng of mage's basc nformaton. H The convoluton template n the experment s H, that s, &' = 6 %' 2 7 ' 2# " Eq. (5) Take H template for example, the (Fgs. 5 and 6) are shown n the followng, respectvely. For the bnarzaton of the fngerprnt mage, we need to fnd a sutable threshold through graythresh functon. When a gray mage s converted nto the bnary mage by the functon m2bw, t's manly to get a sutable threshold by the functon graythresh. The threshold whch s found by the maxmum class varance s more accurate than the facttous settng. In ths paper, we use the former to make a gray mage change nto bnary mage. The (Fg. 7) s the fngerprnt mage before the bnary processng whle the (Fg. 8) s that after the bnary processng. Fg. (7). The fngerprnt mage before bnarzaton. Fg. (5). The fngerprnt mage before hgh pass flterng. Fg. (8). The fngerprnt mage after bnarzaton. Fg. (6). The fngerprnt mage after hgh pass flterng The Bnarzaton Of The Fngerprnt Image After bnarzaton, t can reduce a lot of useless nformaton for fngerprnt dentfcaton, and t can be classfed accordng to the enhanced characterstc nformaton at the same tme. Therefore the bnarzaton of the fngerprnt mage can mprove the effcency of recognton. The theory of mage's bnarzaton s as follows. Set a grey level as the threshold n mage gray scale. They are recorded as nput mage f( and output mage F(, respectvely. The sngle threshold segmentaton algorthm s as follows. It's the bnarzaton program below. level=graythresh(sharp), %Calculate the bnarzaton threshold bw=m2bw(sharp,level), %the bnarzaton mage fgure, mshow(bw) To make a further processng, such as to fll the small holes n the mage streaklnes, to make the fuzzy regon n the bnary mage clear and remove the pores and cavty fll, we can get the fngerprnt mage (Fgs. 9 and 0) as shown below. #, f ( > T F( = " 0, f ( T Eq. (6) Fg. (9). The fngerprnt mage before modfyng.

4 0 The Open Automaton and Control Systems Journal, 205, Volume 7 Nng Lu The thnnng program s as follows. thnned=thn4(decorated), %the thnnng mage fgure, mshow(thnned) Fg. (0). The fngerprnt mage after modfyng. The program of removng pores and cavty fll s gven as the followng. decorated=decorate(bw);% Modfy the mage fgure, mshow(decorated) 2.5. The Thnnng Of The Fngerprnt Image After bnarzaton, the mage nformaton doesn't exaggerate the trend of streamlne. And the streamlne has a larger wdth. It's not conducve to extract the feature nformaton. Therefore, the mage thnnng s very mportant. After thnnng, the fngerprnt mage can reduce some useless nformaton to exaggerate ts feature nformaton. The thnnng s used to delete the edge pxel of the streamlne and make streamlne to be sngle pxel. Fnally, t wll repar the thnnng streamlne. Fg. () s changed to be Fg. (2) after thnnng Acqurng Fngerprnt Feature Pont Based On MATLAB The extracton of fngerprnt mage feature pont s to fnd the confrmaton message wth unqueness. That the extracton of feature pont s good or not wll affect the fnal results of the fngerprnt matchng. We adopt the thnnng mage after bnarzaton n ths paper. The method of feature pont's extracton s that Mn(P) s set to be the crossng number and Sn(P) s pxel 8 neghborhood. They are shown as (Fgs. 3 and 4) below. Fg. (3). The ntersecton pont and endpont. Fg. (4). The 8 neghborhood of P. 8 Mn( P) = = ( P" " )( = P P9 P 2 ) Eq. (7) Fg. (). The fngerprnt mage before thnnng. Fg. (2). The fngerprnt mage after thnnng. Sn( P) = = P 8 Eq. (8) After thnnng completely, fngerprnt mage has three streaklnes ponts,t hat's, endpont, combo pont and ntersecton pont. Where, when Mn(P)=, Sn(P)=3, they are called the endponts; when Mn(P)=2,Sn(P)=2, 3, 4, they are called the combo ponts; when Mn(P)=3, Sn(P)=3, they are called the ntersecton ponts. Assume that P(P, P2,..., Pn) s used to express a set of the feature ponts. Where, P=(X Y T A), and X Y are used to express the coordnates of the feature ponts, respectvely; T s used to express the type of the feature ponts;n s the number of feature ponts. When the feature ponts are the endponts, T=,whle they are the ntersecton ponts, T=2.

5 Research and Applcaton of Fngerprnt Recognton Based on Matlab The Open Automaton and Control Systems Journal, 205, Volume The Expermental Procedure And The Result The extracton program of fngerprnt mage feature s gven below Fgs. (5 and 6). Calculate the number of spots n the asjacent pont Dsplay the ntersecton pont and endpont Fnd the ntersecton pont and endpont Experment for (6) Fg. (5). The expermental procedure. Remove edge effect Record three black asjacent pont of the ntal bfurcaton pont Remove breakpont Remove flash and holes and so on Fg. (6). The extracton of fngerprnt mage feature. mnutae=feat(thnned), % search for feature pont nclude endpont and bfurcaton pont fgure, mshow (mnutae). CONCLUSION In ths paper, t's analyzed systemcally for the mage segmentaton, mage enhancement, mage bnarzaton, mage thnnng and the extracton of fngerprnt mage feature pont based on Matlab. CONFLICT OF INTEREST The authors confrm that ths artcle content has no conflct of nterest. ACKNOWLEDGEMENTS Ths work s supported by the basc and fronter technology research project of Henan and Technology Department( ) and the basc research project of Henan and Technology Department(204B520067). REFERENCES [] R. C. Hum, An dentfcaton n nformaton systems: management challenges an publc polcy ssues, Informaton Technology and People, vol. 7, no. 04, pp. 6-37, 994. [2] Z. Chen, and C.H.Kuo, Atoplogy-based matchng authentcaton, IEEE, vol. 9, 99. [3] N. K. Ratha, S. Y. Chen, A. K. Jan, Adaptve flow orentatonbased feature extracton n fngerprnt mages, Pattern Recognton, vol. 28, no. 0, pp , 995. [4] J. Y. Guo, Q. Wu, and Q. R. Sang, The detal features extracton of fngerprnt dgtal mage based on Matlab mplementaton, Computer Smulaton, vol. 24, no. 0, pp , [5] T. Mn, The research and applcaton of unversal fngerprnt mage processng and analyzng platform, Computer Engneerng And Desgn, vol. 3, no. 04, pp , 200. [6] W. H. Han, The preprocessng technology n the automatc fngerprnt dentfcaton system, Computer Research and Development, vol. 34, no. 2, pp , 997. [7] H. F. L The reasearch of adaptve bnarzaton algorthm for the fngerprnt mage based on drected graph, Bejng Normal Unversty(Natural Scennce edton), vol. 45, no. 03, pp , [8] J. M. Su, Matlab 7.0 Practcal Gude, Electronc Industry Press: Bejng, Receved on: May 26, 205 Revsed on: July 4, 205 Accepted on: August 0, 205 Nng Lu; Lcensee Bentham Open. Ths s an open access artcle lcensed under the terms of the ( whch permts unrestrcted, non-commercal use, dstrbuton and reproducton n any medum, provded the work s properly cted.