Improved Methods on PCA Based Human Face Recognition for Distorted Images

Transcription

1 Poceedngs of the Intenatonal MultConfeence of Engnees and Compute Scentsts 016 Vol I,, Mach 16-18, 016, Hong Kong Impoved Methods on PCA Based Human Face Recognton fo Dstoted Images Buce Poon, M. Ashaful Amn, and Hong Yan Abstact hs pape examnes vaous llumnaton nvaant technques and dentfes the one whch woks well wth pncple component analyss fo human face ecognton. Expemental esults show that by applyng the technque called Gadentfaces at the pe-pocessng stage whch computes the oentaton of the mage gadents n each pxel of the face mages and uses the computed face epesentaton as an llumnaton nvaant veson of the nput mage, t can geatly mpove the ecognton ates. Fom a low ecognton ate of 6.5% up to 60.75% testng on the Asan face database whch has mages wth vaous llumnaton. Index ems Face ecognton, pncple component analyss (PCA), gadentfaces, llumnaton nsenstve measue. I I. INRODUCION LLUMINAION s pobably one of the man poblems fo human face ecognton. In ou pevous eseach wok [1, 4, 5], we had dentfed that poblem. A souce of lght can affect facal featues. Some of them may appea to dmnsh n cetan cases. In the past, a lot of woks had been done to solve that poblem. II. RELAED WORKS Jobson et al. [] poposed the sngle scale etnex (SSR) algothm. hs photometc nomalzaton technques s based on the so-called etnex theoy [3]. he mult scale etnex (MSR) algothm whch s an extenson of the sngle scale etnex algothm agan poposed by Jobson et al. [4]. Pak et al. [5] poposed the adaptve sngle scale etnex (ASR) algothm whch was one of the newest addtons to the etnex technques. Homomophc flteng (HOMO) s a well known nomalzaton technque whee the nput mage s fst tansfomed nto the logathm and then nto the fequency doman. Hee, the hgh fequency components ae emphaszed and the low-fequency components ae educed. As a fnal step, the mage s tansfomed back nto the spatal doman by applyng the nvese Foue tansfom and takng the exponental of the esult. A moe detaled descpton of Buce Poon s wth the School of Electcal & Infomaton Engneeng, Unvesty of Sydney, NSW 006, Austala (e-mal: buce.poon@eee.og). M. Ashaful Amn s wth the Compute Vson & Cybenetcs Reseach Goup, SECS, Independent Unvesty Bangladesh, Bashundhaa, Dhaka 19, Bangladesh. (e-mal: amnmdashaful@ub.edu.bd). Hong Yan s wth the Depatment of Electonc Engneeng, Cty Unvesty of Hong Kong, Hong Kong, Chna (e-mal:h.yan@ctyu.edu.hk) the technque can be found n [6]. Wang et al. [7] ntoduced the sngle scale self quotent mage (SSQ) to the feld of face ecognton. hs technque exhbts smlates to the sngle scale etnex technque, but unlke SSR technque, t uses an ansotopc flte fo the smoothng opeaton. Lke the SSQ technque, the mult scale self quotent mage (MSQ) was also ntoduced to the feld of face ecognton by Wang et al. [7]. he technque exhbts smlates to the mult scale etnex technque, but unlke the MSR technque, t uses an ansotopc flte fo the smoothng opeaton. Chen et al. [8] poposed the dscete cosne tansfom (DC) based nomalzaton technque. hs technque sets a numbe of DC coeffcents coespondng to lowfequences to zeo and hence tes to acheve llumnaton nvaance. Du & Wad [9] poposed the wavelet based (WA) nomalzaton technque. hs technque apples the dscete wavelet tansfom to an mage and then pocesses the obtaned sub-bands. It emphaszes the matces of detaled coeffcent and apples hstogam equalzaton to the appoxmate coeffcents of the tansfom. Afte the manpulaton of the ndvdual sub-band, the nomalzed mage s econstucted usng the nvese wavelet tansfom. Zhang et al. [10] poposed the wavelet denosng (WD) based nomalzaton technque. hs technque apples wavelet denosng to an mage to obtan an estmate of the lumnance and consequently to compute the eflectance. Goss and Bajovc [11] poposed the sotopc dffuson (IS) based nomalzaton technque whch uses sotopc smoothng of the mage to estmate the lumnance functon. It epesents a smple vaant of the ansotopc dffuson based nomalzaton technque. A moe detaled descpton of the technque can be found n [6]. he ansotopc dffuson (AS) based nomalzaton technque whch uses ansotopc smoothng of the mage to estmate the lumnance functon was agan ntoduced to the feld of face ecognton by Goss and Bajovc [11]. he modfed ansotopc dffuson (MAS) based nomalzaton technque epesents a modfed veson of the ansotopc dffuson based nomalzaton technque was agan poposed by Goss and Bajovc [11]. wo modfcaton wee ntoduced nto the technque when compaed to the ognal appoach : () the estmate of the local contast was made moe obust by ntoducng an addtonal atan functon. hs has the effect of satuatng the exteme values that ae ntoduced to the contast estmate due pxel ntenstes nea 0 n the ognal face mages. () a obust postpocessng pocedue [1] was appled n the fnal stage of the technque. Feeman and Adelson [13] poposed the steeable flte (SF) based nomalzaton technque whch uses steeable

2 Poceedngs of the Intenatonal MultConfeence of Engnees and Compute Scentsts 016 Vol I,, Mach 16-18, 016, Hong Kong fltes fo emovng llumnaton nduced appeaance vaatons fom the facal mages. Stuc and Pavesc [14] poposed the non-local means [NLM] based nomalzaton technque whch uses the non-local means denosng algothm to compute the lumnance functon and consequently to estmate the eflectance. he adaptve non-local means (ANL) was agan poposed by Stuc and Pavesc [14] whch uses the adaptve non-local means denosng algothm to compute the lumnance functon and consequently to estmate the eflectance. Hee, the adaptveness of the smoothng s contolled by the mages local contast. Zhang et al. [15] poposed the gadentfaces (GRF) based nomalzaton techque whch computes the oentaton of the mage gadents n each pxel of the face mages and uses the computed face epesentaton as an llumnaton nvaant veson of the nput mage. Wang et al. [16] poposed the sngle scale Webefaces (WEB) nomalzaton technque whch computes the elatve gadent n the fom of a modfed Webe contast and uses the computed face epesentaton as an llumnaton nvaant veson of the nput mage. he mult scale Webefaces (MSW) s a staght fowad extenson of the sngle scale Webefaces appoach also poposed by Wang et al. [16]. he functon computes the elatve gadent n the fom of a modfed Webe contast fo dffeent neghbohood szes and uses a lnea combnaton of the computed face epesentatons as an llumnaton nvaant veson of the nput mage. Xe et al [17] poposed the lage and small-scale featues (LSSF) nomalzaton technque whch nomalzes the nput mage by fst computng the eflectance and lumnance functons of the mage and then futhe pocessng both computed functons usng a second ound of nomalzaton. SSR technque s beng used n both steps, but does not mplement the non-pont lght technque whch eques tanng data that would lmt the applcablty of the technque to fontal mages. an and ggs [1] poposed the an and ggs () nomalzaton technque whch nomalzes the nput mage though the use of a pocessng chan that fst apples gamma coecton to the nput mage, then subjects the coected mage to dffeence of Gaussans (DoG) flteng and fnally employs a obust post-pocesso to poduce the fnal esult. he DoG flteng-based nomalzaton technque eles on the dffeence of Gaussans flte to poduce the nomalzed mage. Bascally t apples a bandpass flte to the nput mage and poduces a nomalzed veson of t. Shaf et al. [18] poposed an llumnaton nomalzaton technque whch woks at the pe-pocessng stage whee the face mage s fst dvded nto equal sub-egons. Each subegon s then pocessed sepaately fo llumnaton nomalzaton. he segments ae then joned back follow futhe pocessng lke nose, emoval and contast enhancement. he INface toolbox povded by Stuc [19], [0] has a collecton of vaous llumnaton nomalzaton technques. Afte evaluaton and testng, we have dentfed that gadentfaces (GRF) based nomalzaton techque woks best wth pncple component analyss fo human face ecognton. Detals of woks and expements ae beng descbed n the followng sectons. A. System Stuctue III. PROPOSED ECHNIQUE o handle the llumnaton nomalzaton poblem fo facal ecognton, ths pape poposes to add the Gadentfaces based nomalzaton technque [15] n the pepocessng stage n ode to compute the oentaton of the mage gadents n each pxel of the face mages and uses the computed face epesentaton as an llumnaton nvaant veson of the nput mage. A typcal facal ecognton system wth fou majo genec components and an addtonal llumnaton nomalzaton module s shown n Fgue 1. Facal Data Acquston Illumnaton Nomalzaton Facal Data Pe-pocessng Fg. 1 A genec facal ecognton system wth llumnaton nomalzaton B. Facal Image Acquston Facal Featue Extacton Facal Recognton o Classfcaton In ou pevous wok [1], we had dentfed the poblem wth llumnaton on face mages fom the Asan Face Database [1]. We utlzed the same face database n ode to compae the dffeences n expemental esults. Fo the Asan Face Database, we have selected the followng thee goups, a) Faces wth vaous expessons and slght dffeent llumnaton; b) Faces wth vaous poses and slght dffeent llumnaton; and c) Faces wth fontal mages but vaous llumnaton condtons. Fo each goup, thee ae ten dffeent algned mages of each of 40 dstnct pesons. he sze of each mage s pxels, wth 56 gay levels pe pxel. Examples ae povded n Fgues., 3 and 4. Fg. Sample mages fo a subject of the Asan Face Database wth vaous facal expessons and slghtly dffeent llumnaton Fg. 3 Sample mages fo a subject of the Asan Face Database wth vaous poses and slghtly dffeent llumnaton

3 Poceedngs of the Intenatonal MultConfeence of Engnees and Compute Scentsts 016 Vol I,, Mach 16-18, 016, Hong Kong Smlaly, we have I ( x, y R( x, L(x, y (6) Fg. 4 Sample mages fo a subject of the Asan Face Database wth fontal mages but vaous llumnaton condtons (fom bght to dak) C. Facal Images Pepocessng In ths pepocessng stage, we add the Gadentfaces based nomalzaton technque [15] n ode to extact the llumnaton nsenstve measues whch wll be descbed as follow : c.1 Reflectance Model : he eflectance Model used n many cases can be expessed as I(x, = R(x, L(x, (1) whee I(x, s the mage pxel value, R(x, s the eflectance and L(x, s the llumnance at each pont (x,. Hee, the natue of L(x, s detemned by the lghtng souce, whle R(x, s detemned by the chaactestcs of the suface of object. heefoe, R(x, can be egaded as llumnaton nsenstve measue. Sepaatng the eflectance R and the llumnace L fom eal mages s an ll-posed poblem. In ode to solve the poblem, a common assumpton s that L vaes vey slowly whle R can change abuptly. c. Gadentfaces : In ode to extact llumnaton nsenstve measue fom gadent, we have the followng theoem by studyng the elatonshps between the components of gadent doman. heoem 1 : Gven an abtay mage I(x, taken llumnaton condton, the ato of y-gadent of I(x, (I(x, / to x-gadent of I(x, (I(x, /x) s an llumnaton nsenstve measue. Poof : Consdeng two neghbong ponts (x, and (x+ x, ), accodng to the llumnaton model (1), we have I(x, = R(x, L(x, () I(x+ x, = R(x+ x, L(x+ x, (3) Subtactng () fom (3), we obtan I(x+ x, - I(x, = R(x+ x, L(x+ x, - R(x, L(x, Based on the above-mentoned common assumpton, whch means L s appoxmately smooth, we have I(x+ x, - I(x, R(x+ x, L(x, - R(x, L(x, (R(x+ x, - R(x, ) L(x, (4) akng the lmtaton of the above equalty (4), we can obtan I ( x, R( x, L(x, (5) x x Dvdng (6) by (5), we have I ( x, y ) y I ( x, y ) x R ( x, y ) y R ( x, y ) x Accodng to llumnaton model (1), R can be consdeed as an llumnaton nsenstve measue. hus, the ato of y- gadent of I(x, I( x, y to x-gadent of I(x, I( x, x s also an llumnaton nsenstve measue. In pactcal applcaton, the ato of y-gadent of mage to x-gadent of mage mght be nfntude deved by zeo value of x-gadent of mage. heefoe, t cannot be dectly used as the llumnaton nsenstve measue. hese consdeatons lead us to defnng Gadentfaces as follows. Defnton 1 : I be an mage unde vaable lghtng condtons, then Gadentfaces (G) of mage I can be defned as I y gadent G = actan, G [0, π ) (8) I x gadent Whee I x-gadent and I y-gadent ae the gadent of mage I n the x, y decton, espectvely. c.3 Implememtaton : In ode to extact Gadentfaces, we need fstly to calculate the gadent of face mage n the x, y decton. Gadentfaces can then be computed by the defnton (8). hee ae many methods fo calculatng the gadent of mage. Howeve, the numecal calculaton of devatve (gadent) s typcally ll-posed. o compute the gadent stably, we smoothen the mage fst wth Gaussan kenel functon. Wth a convoluton-type smoothng, the numecal calculaton of gadent s much moe stable n calculaton. he man advantage fo usng Gaussan kenel s twofold: (a) Gadentfaces s moe obust to mage nose and, (b) t can educe the effect of shadows. he mplementaton of Gadentfaces can be summazed n able I. able I Implementaton of Gadentfaces Input: Image I Output: he Gadentfaces of I 1. Smoothen nput mage by convolvng wth Gaussan kenel functon : I = I * G(x, y, σ), and save you gaphc mages usng a sutable whee * s the convoluton opeato and gaphcs pocessng G(x, y, σ) = pogam (1 / π σ ) that exp ( wll - (x + allow y ) / you σ ) to ceate the mages s Gaussan as PostScpt kenel functon (PS), wth Encapsulated standad devaton PostScpt σ. (EPS),. Compute the gadent of mage I by feedng the smoothed mage o agged Image Fle Fomat (IFF), szes them, and adjusts though a convoluton opeaton wth the devatve of Gaussan the esoluton kenel functon settngs. the x, y If dectons: you ceated you souce fles n one of the followng I x = I you * G x(x, wll y, σ), be and able I y = I * to G y(x, submt y, σ), the gaphcs whee G wthout convetng x(x, y, σ) and G to y(x, y, σ) ae the devatve of Gaussan kenel functon n the x, y a dectons, PS, EPS, espectvely. o IFF fle: Mcosoft Wod, 3. Compute Mcosoft the llumnaton PowePont, nsenstve Mcosoft measue by Excel, o Potable G = actan (I y / I x ) [0, π ). 4. Obtan Gadentfaces G. (7)

4 Poceedngs of the Intenatonal MultConfeence of Engnees and Compute Scentsts 016 Vol I,, Mach 16-18, 016, Hong Kong Fg. 5 Sample mages fo a subject of the Asan Face Database wth fontal mages but vaous llumnaton condtons (fom bght to dak) (uppe ow) and the coespondng Gadentfaces pocessed mages (lowe ow) Fgue 5 shows the ognal mages and the coespondng Gadentfaces pocessed mages. Gadentfaces can extact the mpotant featues of face, such as facal shapes and facal objects (e.g., eyes, noses, mouths, and eyebows) unde vaous lghtng condtons, whch ae key featues fo face ecognton. heefoe, Gadentfaces s an llumnaton nsenstve measue. D. Facal Featue Extacton usng pncple component analyss (PCA) Intal featue of a facal mage s the gay ntensty of each pxel. Each facal mage s conveted nto a ow vecto by appendng each ow one afte anothe. Fo the Asan database whch has facal mages geomety nomalzed and llumnaton nsenstve measues extacted by the Gadentfaces technque has mage sze of 40 x 50. It wll become a,000 dmensonal featue vecto whch s vey hgh fo any classfcaton technque to be appled n ode to lean the undelyng classfcaton ules. heefoe, pncple component analyss (PCA) s appled to extact moe elevant featues/sgnatues []. Pncple component analyss (PCA) s a smple statstcal method to educe the dmensonalty whle mnmzng mean squaed econstucton eo []. Let us assume that M facal mages that ae denoted as Ι 1, Ι,..., Ι M have sze a b pxels. Usng conventonal ow appendng method, we convet each of the mages nto N a b = dmensonal column vecto. At fst the mean mage as column vecto, Ξ of sze N, fom all the mage vectos of s calculated as shown n Equaton (9). Ξ = 1 M Ι M = 1 hen each face dffeence fom the aveage s calculated usng the equaton (10). (9) a Ι Ξ (10) = We then constuct the matx A = [ a a,..., ] 1, contanng all the mean-nomalzed face vectos as columns. Usng ths nomalzed face vectos we can calculate the covaance matx I along the featue dmenson of sze N N of all the featues usng the followng conventonal fomula as: a M I = 1 (11) N ΑΑ Hee notce that the matx ΑΑ of sze needed to be constucted to calculate the matx I. Howeve, t s vtually mpossble fo the memoy ΑΑ constans to pefom any matx opeaton on the matx. Rathe, the method descbed n [3] s employed to constuct the matx ℵ usng Equaton (1). Instead of ΑΑ, the matx Α Α of sze 360x 360 (out of 400 mages 10 fo each subject, 40 mages one fo each subject s kept apat fo testng) s constucted as ℵ of sze M M usng: ℵ = 1 M Α Α (1) hen we calculate the egenvalue and egenvectos of ths covaance matx usng Equaton (13). [, D] = egs( ℵ) V (13) Hee, d, d,..., d ] D = of sze M contans the [ 1 M soted egenvalues, such that d d... d 1 M and the coespondng egenvectos of the matx ℵ s contaned n the matx V [ v v,..., ] = 1, v M whch s of sze M M. Accodng to the method poposed n [4], we can acque the coespondng egenvectos of the matx I usng V = v v,..., as: [ ] 1, v M U A V = (14) Hee notce that, even though each vecto M, the vectos v s of sze u of U = u, u,..., u ] ae of sze N. [ 1 M We can use the matx U to poject ou N data onto lowe M dmensons. he pojected data fom the ognal N dmensonal space to a subspace spanned by pncpal egenvectos (fo the top egenvalues) contaned n the matx Ω expessed as: Y = Ω A (15) In ou pevous eseach wok [1], we chose the top 50 pncple components as featues n the lowe dmenson as the sum of the top 50 egenvalues of the covaance matx s moe than 90% of the sum of all the egenvalues. E. Facal Recognton o Classfcaton When all the facal mages ae fnally epesented wth elevant featues by pojectng onto a lowe dmenson usng PCA, we can use smlaty measues between faces fom the same ndvdual and dffeent ndvduals. Assume that the nomalzed vecto fomed face test mages ae kept n the matx (note that thee ae 40 mages fo 40 subjects that wee not used n the PCA stage), whee each column coesponds to a test face mage. Fo classfcaton, we fst

5 Poceedngs of the Intenatonal MultConfeence of Engnees and Compute Scentsts 016 Vol I,, Mach 16-18, 016, Hong Kong nomalze the test mages vecto by subtactng the mean calculated pevously (Equaton (9)) usng: B = Ξ (16) hen usng Equaton (15) we poject the nomalzed test data set as shown n the followng equaton. Z = Ω B (17) Fo each column n the matx Z, we calculate the Eucldean Nom of the dffeence wth the pojected vectos of matxy. Fnally, the test mage s dentfed as the peson wth the smallest value among all the Eucldean Nom values. IV. EXPERIMENAL RESULS AND DISCUSSION Fgues 6, 7 & 8 show the ecognton accuacy wth & wthout Gadentfaces pepocessng unde vaous condtons In Fgue 7, fo face database wth vaous poses and slghtly dffeent llumnaton, thee s a bg mpovement n ecognton accuacy wth Gadentfaces llumnaton nomalzaton n the pepocessng stage, fom 15.50% to 36.50%. % Accuacy Numbe of sgnatues Wth pepocessng Wthout pepocessng Fg. 8 Recognton accuacy wth and wthout Gadentfaces pepocessng fo the Asan Face Database wth fontal mages but vaous llumnaton condtons (fom bght to dak) % Accuacy Numbe of sgnatues Wth Pepocessng Wthout Pepocessng Fg. 6 Recognton accuacy wth and wthout Gadentfaces pepocessng fo the Asan Face Database wth vaous facal expessons and slghtly dffeent llumnaton In Fgue 6, fo face database wth vaous facal expessons and slghtly dffeent llumnaton, thee s a slght mpovement n ecognton accuacy wth Gadentfaces llumnaton nomalzaton n the pepocessng stage, fom 51.75% to 59.75%. % Accuacy Numbe of sgnatues Wth Pepocessng Wthout Pepocessng Fg. 7 Recognton accuacy wth and wthout Gadentfaces pepocessng fo the Asan Face Database wth vaous poses and slghtly dffeent llumnaton In Fgue 8, fo face database wth fontal mages but vaous llumnaton, thee s a much bgge mpovement n ecognton accuacy wth Gadentfaces llumnaton nomalzaton n the pepocessng stage, fom 6.5% to 60.75%. he esults ae summazed n able II. able II Summay of testng esults Condtons Recognton accuacy wthout Recognton accuacy wth % of mpovement pepocessng pepocessng Vaous 51.75% 59.75% 15.45% Expesson Vaous Poses 15.50% 36.50% 35.48% Vaous 6.5% 60.75% 97.00% Illumnaton V. CONCLUSIONS Illumnaton has been a majo poblem on ou PCA based human face ecognton. Wth llumnaton nomalzaton technque n the facal mage pepocessng stage to extact the llumnaton nvaant featues, t mpoves the ecognton ate. Among all the llumnaton nomalzaton technques we have evaluated, Gadentfaces has been dentfed as the one whch woks well wth ou PCA based human face ecognton system. It geatly mpoves the ecognton ate especally those mages unde vaous llumnaton condtons, fom a low ecognton ate of 6.5% to 60.75%. Apat fom facal mages wth vaous llumnaton, dstoted mages also nclude nosy & bluy mages. Wth the chaactestc of Gadentfaces nomalzaton technque, futhe eseach woks wll be done on those nosy & bluy facal mages f ths Gadentfaces can also wok well wth ou PCA based human face ecognton system.

6 Poceedngs of the Intenatonal MultConfeence of Engnees and Compute Scentsts 016 Vol I,, Mach 16-18, 016, Hong Kong REFERENCES [1] B. Poon, M. A. Amn and H. Yan, Pefomance evaluaton and compason of PCA based human face ecognton methods fo dstoted mages, Intenatonal Jounal of Machne Leanng and Cybenetcs, Volume, Issue 4 (011) p.45 p.59. [] D. J. Jobson, Z. Rahman, G.A. Woodell, Popetes and pefomance of a cente/suound etnex, IEEE ansactons on Image Pocessng, Vol. 6, No.3, pp , [3] E. R. Land, J.J. McCann, Lghtness and etnex theoy, Jounal of the Optcal Socety of Ameca, Vol. 61, No.1, pp. 1-11, [4] D. J. Jobson, Z. Rahman, G.A. Woodell, A multscale etnex fo bdgng the gap between colo mages and the human obsevatons of scenes, IEEE ansactons on Image Pocessng, Vol. 6, No. 7, pp , [5] Y. K. Pak, S. L. Pak, J. K. Km, Retnex method based on adaptve smoothng fo llumnaton nvaant face ecognton, Sgnal Pocessng, Vol. 88, No. 8, pp , 008. [6] G. Reusch, F. Cadnaux, S. Macel, Lghtng nomalzaton algothms fo face vefcaton, IDIAP-com 05-03, Mach 005. [7] H. Wang, S. Z. L, Y. Wang, J. Zhang, Self quotent mage fo face ecognton, Poceedngs of the Intenatonal Confeence on Image Pocessng, Vol., pp , 004. [8] W. Chen, M. J. E, S. Wu, Illumnaton compensaton and nomalzaton fo obust face ecognton usng dscete cosne tansfom n logathmc doman, IEEE ansactons on Systems, Man and Cybenetcs - pat B, Vol. 36, No., pp , 006. [9] S. Du, R. Wad, Wavelet-based llumnaton nomalzaton fo face ecognton, Poc. of the IEEE Intenatonal Confeence on Image Pocessng, Vol., pp , 005. [10]. Zhang, B. Fang, Y. Yuan, Y. Y. ang, Z. Shang, D. L, F. Lang, Multscale facal stuctue epesentaton fo face ecognton unde vayng llumnaton, Patten Recognton, Vol. 4, No., pp. 5-58, 009. [11] R. Goss, V. Bajovc, An mage pepocessng algothm fo llumnaton nvaant face ecognton, Poc. of the 4th Intenatonal Confeence on Audo and Vdeo-Based Bometc Pesonal Authentcaton, Lectue Notes n Compute Scence, Vol. 688, pp , 003. [1] X. an, B. ggs, Enhanced local textue sets fo face ecognton unde dffcult lghtng condtons, IEEE ansactons on Image Pocessng, Vol. 19, No.6, pp , 010. [13] W.. Feeman, E. H. Adelson, he desgn and use of steeable fltes, IEEE ansactons on Patten Analyss and Machne Intellgence, Vol. 13, pp , [14] V. Stuc, N. Pavesc, Illumnaton nvaant face ecognton by non-local smoothng, Poceedngs of the Bometc ID Management and Multmodal communcaton, Lectue Notes n Compute Scence, Vol. 5707, pp. 1-8, 009. [15]. Zhang, Y.Y. ang, B. Fang, Z. Shang, X. Lu, Face ecognton unde vayng llumnaton usng gadentfaces, IEEE ansactons on Image Pocessng, Vol. 18, No. 11, pp , 009. [16] B. Wang, W. L, W. Yang, Q. Lao, Illumnaton nomalzaton based on webe's law wth applcaton to face ecognton, IEEE Sgnal Pocessng Lettes, Vol. 18, No.8, pp , 011. [17] X. Xe, W. S. Zheng, J. La, P. C. Yuen, C. Y. Suen, Nomalzaton of face llumnaton based on lage- and smallscale featues, IEEE ansactons on Image Pocessng, Vol. 0, No.7, pp , 011. [18] M. Shaf, S. Mohsn, M. J. Jamal, M. Raza, Illumnaton Nomalzaton Pepocessng fo face ecognton, nd Confeence on Envonmental Scence and Infomaton Applcaton echnology, pp , 010. [19] V. Stuc, N. Pavesc, Photometc nomalzaton technques fo llumnaton nvaance, In: Y.J. Zhang (Ed.), Advance n Face Image Analyss : echnques and technologes, IGI Global, pp , 011 [0] V. Stuc, N. Pavesc, Gabo-Based Kenel patal-least-squae Dscmnaton Featues fo Face Recongton, Infomatca (Vlnus), vol. 0, no.1, pp , 009. [1] Asan face database fom Intellgent Meda Laboatoy [] M. uk and A. Pentland, Egenfaces fo Recognton, Jounal of Cogntve Neuoscence, Vol. 13, No.1, pp , [3] R. Chellapa, C. L. Wlson and S. Sohey, Human and machne ecognton of faces: a suvey, Poc. IEEE, pp , 1995 [4] B. Poon, M. A. Amn and H. Yan, PCA based face ecognton and testng ctea, ICMLC, Vol. 5, pp , 009. [5] M. A. Amn and H. Yan, An empcal study on the chaactestcs of gabo epesentatons fo face ecognton, Intenatonal Jounal of Patten Recognton and Atfcal Intellgence, vol. 3, No. 3, pp , 009.