A New Method To Improve Movement Tracking Of Human Sperms

Transcription

1 IAENG Iteratoal Joural of Computer Scece, 45:4, IJCS_45_4_05 A New Method To Improve Movemet Trackg Of Huma Sperms I Gede Susrama Masdyasa, Member, IAENG, I Ketut Eddy Purama, Maurdh Hery Puromo Abstract Oe of the determats of sperm qualty s the motlty of spermatozoa. The motlty of spermatozoa s measured by mcroscopc sperm test. Covetoally; the determato of sperm motlty s performed by experts, whch the judgmet teds to be subjectve. The exstece of Computer-Asssted Sperm Aalyss (CASA) s beefcal solvg problems related to the emergece of subjectvty the determato of sperm motlty. Geerally, CASA ad researchers ths feld use phase cotrast mcroscopes to obta mages wth hgher cotrast. I ths study, the posto ad motlty determatos of spermatozoa the vdeo were performed usg vdeo records take from a brght feld mcroscope wth low cotrast, alog wth varous other defceces. Wth a combato of several stages of works, amely frame dfferece backgroud subtracto, cotrastsettg wth Otsu threshold as a dcator, flterg process usg mathematcal morphology to determe the posto of objects, as well as lear regresso ad root mea square value (RMS) calculatos. From the results of expermetal tests performed o huma spermatozoa vdeo data, the above method dcated that the postos of sperm motlty from trackg results had recogzable trajectores based o the average dstace posto to the lear regresso le, wth a RMS threshold of 0. There were te progressve spermatozoa ad four o-progressve spermatozoa. The method used successfully determed 4 huma spermatozoa. There were 7% progressve spermatozoa, whle the remag 9% were o-progressve. Uder the WHO 00 gudeles, a 7% percetage dcates ormal sperm motlty. Idex Terms Spermatozoa, Lear Regresso, Root Mea Square, Backgroud Subtracto, Mathematcal Morphology I. INTRODUCTION Sperm examato s oe of the easest ways to fd out the fertlty or fertlty of a male. The level of Afertlty s geerally assocated wth a male's ablty to produce offsprg. A test of spermatozoa aalyss to measure fertlty o the husbad s performed a laboratory. Oe of the objectves of ths test s to determe the mperfect shape ad motlty of sperm. The sperm must be perfectly shaped ad able to move quckly ad accurately to the ovum to trgger the fertlzato process. Whe the form ad structure (morphology) are ot stadard, or the motlty s ot perfect, the the sperm caot reach or Mauscrpt receved Jauary 0, 08; revsed September 9, 08. I Gede Susrama Masdyasa s wth Departmet of Electrcal Egeerg, Isttut Tekolog Sepuluh Nopember, Surabaya Idoesa, Emal: susrama@mhs.ee.ts.ac.d I Ketut Eddy Purama s wth Departmet of Electrcal Egeerg ad Departmet of Computer Egeerg, Isttut Tekolog Sepuluh Nopember, Surabaya Idoesa, Emal: ketut@ee.ts.ac.d Maurdh Hery Puromo s wth Departmet of Electrcal Egeerg ad Departmet of Computer Egeerg, Isttut Tekolog Sepuluh Nopember, Surabaya Idoesa, Emal: hery@ee.ts.ac.d. peetrate the egg. Geerally, ormal sperm ca swm at a speed of.5 cm every 5 mutes []. Spermatozoa aalyss procedures commoly practced today have costrats whe assocated wth low-qualty acqusto devces ad lmted magfcato modes. The maual method has dffcultes determg the level of abormaltes of sperm motlty because the motlty of each spermatozoo eed to be tracked ad ther speed to be calculated. The use of computers has bee employed to address the ssues related to experts, o a system kow as the Computer-Aded Sperm Aalyss (CASA) or sperm aalyzer []. Wth ths system, mcroscopc mages of seme are take, whch are the aalyzed regardg cocetrato (sperm cout), moblty, ad morphology. The parameters tested usg CASA clude the calculato of spermatozoa, determato of movemet aglty (motlty), ad determato of spermatozoa morphology. However, commercal CASA products are stll too expesve. These products are also mperfect. The accuracy of the aalyss s hghly depedet o the qualty of the supply of seme. The low qualty of seme supply decreases the accuracy of spermatozoa calculatos ad the determato of motlty levels. Also, these commercal products stll caot perform automatc spermatozoa classfcato based o the estmate ad judgmet of motlty to the ormal, less tha ormal, or abormal classes. Several studes relatg to spermatozoa aalyss had begu 988. The early geerato was called CASMA (Computer Aded Sperm Motlty Aalyss), whch used a cotrast phase lghtg mcroscope [3] [4]. I Doald T. S., et al. (988), the early geerato sperm aalyzer used aalog recordg, segmetato, ad trackg betwee two frames. The motorg of spermatozoa the ext frame compares the frame of trackg by takg to accout the maxmum speed of motlty of spermatozoa betwee frames. The separato of spermatozoa s doe based o the posto of each spermatozoa ad marker cotaed by each spermatozoo. Durg the trackg process, vdeo recordg s dsplayed o the scree. The spermatozoa head mssg durg trackg wll be marked (+) at the last posto so that the laboratory attedat ca evaluate the trackg accuracy. Ths system ca track wth a accuracy of 85%. There are several dsadvatages to ths system, amely: the umber of spermatozoa durg the process s lmted, o real-tme results, ad there are escapg spermatozoa durg the trackg process. Ths study was cotued by J. L. Yáza, et al., who developed CASMA usg dgtally recorded spermatozoa vdeo [3]. A few years later, a system called RSTS (Real Tme Spermatozoa Tracg System) [5] by S. T. Youg, et al. (998) was troduced to overcome the costrats the sperm aalyzer system. RSTS, as the ame mples, was developed wth a real-tme observato method whe the spermatozoa eter the mcroscope's feld of vew ad ts (Advace ole publcato: 7 November 08)

2 IAENG Iteratoal Joural of Computer Scece, 45:4, IJCS_45_4_05 tracks are tracked for a perod of tme. The trackg of the spermatozoa paths provdes formato o the results of measuremets of kematc values that ca be used for the aalyss of sperm motlty. The system uses a cotrast phase lghtg mcroscope to record spermatozoa glowg sphere-lke shapes. The spermatozoa are segmeted usg the gray-level threshold method. Perodcally, the system performs scag the mcroscope vewport the drecto of vertcal les ad horzotal les. If the system fds spermatozoa, the the system wll store the space of vew of the sze ( ) pxels predetermed by the user. The, the spermatozoa wll be moved to the ceter pot of the box. The process cotues utl the spermatozoa dsappear from the mcroscope's feld of vew or utl the maxmum umber of boxes correspods to user put. The total umber of observato frames could reach peces, far more tha most CASA systems at the tme. The system also has some dsadvatages: () the umber of spermatozoa the observato box potetally dsrupts the determato of kematcs of spermatozoa; () box sze determes the speed ad accuracy of spermatozoa trackg. If the box s large, there s the possblty of some spermatozoa collectg oe box, makg t dffcult to calculate the spermatozoa trajectory wth a decrease recordg ablty dow to frames/secod. If the box used s small, the there s the possblty of spermatozoa dsappearg from the trackg process. Tambol, et al. (003) troduced the detecto phase of the movemet of movg mcroscopc objects [6]. As a frst step trackg spermatozoa, the study used several preprocessg steps: the growg rego method for spermatozoa segmetato, creasg cotrast values to clarfy dffereces of spermatozoa from the backgroud, meda flter to reduce ose, ad equalzato flter for seed geerato. Qaolag L, et al. (0) [7], troduced a applcato for detectg ad coutg the umber of huma spermatozoa a vdeo streamg usg Ope CV. The adopted method combed Gaussa-Modelg ad Morphology Method. The algorthm of Gaussa-modelg was used to flter o-target brght objects, whle the mage processg method was adopted to ehace the spermatozoa vdeo mage qualty usg combed methods/algorthms ad real-tme vdeo streamg. Jaqa L, et al. (04) [8], coducted research to detfy the morphology of spermatozoa cells to coclude whether or ot they were healthy. The adopted method was a combato betwee Prcpal Compoet Aalyss (PCA) to extract mage features ad K-Nearest Neghbor (KNN) algorthm to dagose the spermatozoa health. The pctures of the aalyzed spermatozoa cells were take from mcroscopc mages wth very ty szes. The spermatozoa health dagoss comprsed three parts: spermatozoa mage segmetato, extracto of features usg PCA ad spermatozoa classfcato usg the KNN algorthm. The fal results detfed from the research: PCA features ad SHIFT features, KKN classfer, ad BPPN classfer were the compared. The result was that the accuracy of the dagoss depeded o trag sets, as the results of tests wth specfc trag sets proved to geerate excellet performace wth level of accuracy by 87.53% whe compared to the oes wth other feature extracto methods, such as Scale-Ivarat Feature Trasform (SIFT) ad aother classfer, such as Back Propagato Neural Network (BPNN). To cope wth the weakesses of the prevous researches, we propose a ew method to have better spermatozoa trackg. The proposed method cossts of 4 phases: back recostructo, backgroud subtracto, Otsu thresholdg ad mathematcal morphology. The spermatozoa movemet detfcato usg the proposed method was helpful to experts detfyg the umber of sperms. The whole processes are targeted to suggest hghly effcet computato Ravafar et al. [9] used the adaptve temporal meda flter algorthm to separate the backgroud of the vdeo frame by a samplg rate of 30 fps, wth sperm motlty ot beg recorded smoothly. A proposed soluto s to use the temporary Gaussa flter for the trackg process. Vladmr coducted aother research related to object trackg, et al., 03 [0], the applcato for whch ca be see the audece aalyss system to detect faces, face trackg, ad geder recogto ad classfcato. Ths system ca be appled to securty systems that observe huma movemet through vdeo survellace. If compared wth the research coducted, the flow of objects tracked ca go to the reverse drecto, whle the flow of spermatozoa the progressve category s a forward movemet wth a certa speed. From several studes above, the seme vdeo recordg data used o average has a samplg rate of ± 30 fps (frames per secod). Meawhle, to be able to produce data that ca be adequately observed, t takes a sperm vdeo samplg rate of 50 fps. I ths research, sperm vdeo was recorded usg samplg rates above 50 fps. Also, prevous studes were ot coducted o popular sperm vdeo, ad the trackg performed usg lear regresso aalyss, ad RMS (Root Mea Square) curbs had ot bee appled to detfy progressve or o-progressve spermatozoa movemets. Thus, ths research proposed a ew approach to detect ad detfy spermatozoa movemets by modfyg several algorthms for labelg ad umberg processes o spermatozoa, so as to obta a path of sperm moto, whch would be tested by the lear regresso aalyss method to detfy whether a spermatozoo s progressve or oprogressve, the comparg t wth maual calculatos by experts. The detfcato of sperm motlty trackg used TABI (Tme-Averaged Backgroud Image), backgroud subtracto, Otsu Threshold, ad mathematcal morphology. Also, the aalyzed sperm vdeo was recorded usg a brght feld mcroscope devce ad a hgh-speed Pot Gray camera pared a ocular posto ad a objectve les wth 40 tmes magfcato, coected to a laptop as a vdeo processor. II. MATERIAL AND METHODS The research to detfy sperm motlty bega wth the desg of the hardware system. The type of mcroscope used s brght feld mcroscope. Ths system produced spermatozoa motlty recordg vdeo that comprsed the put o the spermatozoa-trackg step utlzg the Tme- Averaged Backgroud Image, backgroud subtracto, Otsu Threshold, ad mathematcal morphology methods. The trackg of spermatozoa yelded a two-dmesoal posto values ad the RMS (root mea square) varable requred to detfy sperm motlty, calculated from the posto of a spermatozoo durg movemet a partcular trajectory, as show Fg.. (Advace ole publcato: 7 November 08)

3 IAENG Iteratoal Joural of Computer Scece, 45:4, IJCS_45_4_05 dffculty s the accuracy of the backgroud obtaed wth real-tme codtos at that tme. If the backgroud s foud oe locato of observato, the the backgroud s used to detect sperm other areas, hece trggerg problems caused by the dscrepacy betwee the backgroud ad realtme codto at that tme caused by the dfferece of locato codtos. Fg. Trackg Process ad Idetfcato of Spermatozoa Abormaltes. A. Data Acqusto All the vdeo capturg process was performed the Itegrated Laboratory of Mcrobology of Health Polytechc of Surabaya. The data used ths study was the form of sperm vdeo obtaed from the results of sperm flud scas of some voluteers. Before beg observed, the sample was frst left asde for about 0-30 mutes [] uder room temperature. It s ecessary because, at the tme of ejaculato, the sperm flud was stll thck ad eeded dluto so that spermatozoa observed would ot be too cocetrated, was able to move more actvely, ad could be dstgushed. The sperm vdeo was captured usg a brght feld mcroscope. The Pot Gray type FL3-U3-3SC-CS camera was placed as a replacemet for the ocular les wth USB 3.0 cable coecto. The researchers used a laptop wth Core 5 processor, 4 GB RAM, ad 500 GB of hard drve capacty as well. Vdeo recordg wth a mcroscope was set usg a objectve les of 40 tmes magfcato so that the motlty of spermatozoa was vsble. The camera ad program settgs were set so that the vdeo had the same cotrast, brghtess, ad whte balace. Also, the mcroscope feld of vew was set to rema mmoble durg the recordg process. The resultg vdeo was saved ad the coverted to the be processed. Because the computer could ot match performace wth the frame rate of the vdeo, sometmes there was slowess to up to e frames a row. The result was stutterg vdeo mage, where the movemet of the objects becomes jumpy (ot smooth). A llustrato of ths process s Fg.. B. Backgroud Recostructo The system's ablty to separate the backgroud ad foregroud the form of movg spermatozoa s eeded to detfy movg sperm. Backgroud retreval was doe by scag whe o sperm was rug. Backgroud retreval ths way creates (two) sgfcat dffcultes. The frst dffculty s the process of retrevg the backgroud because t s challegg to obta the codto wthout movg sperm or o sperm at all. It s ot possble to stop all sperm from gettg the desred backgroud. The secod Fg. Real-tme process of spermatozoa vdeo data collecto Some researchers had researched backgroud recostructo or preprocessg usg a seres of moto pctures, such as Akara S. et al. (0), that cofrmed the eed for preprocessg the detecto of dabetc retopathy dsease by observg retal mage textures []. The mage data used had a ueve cotract, so the Cotrast Lmted Adaptve Hstogram Equalzato method ad shade correcto algorthm was appled. Smlarly, Korprobst et al., (999), stated that the backgroud s the most frequetly see mage of a seres of movg mages. I other words, backgroud formers have the most frequet frequecy of occurreces [3]. Meawhle, Log et al. (990) stated that the backgroud has a stable testy for a log tme [4], as well as Gloyer et al. (995), who stated that the backgroud would at least be see more tha 50% of a seres of movg mages [5] From several assumptos above, t ca be cocluded that the backgroud ca be obtaed by takg the average value of a seres of mages. The average value wll be close to the desred backgroud mage. Thus, ths research used the TABI (Tme-Averaged Backgroud Image) method [6] to coduct preprocessg or backgroud recostructo. The steps to retreve backgroud by separatg t from foregroud based o sperm vdeo ca be explaed as follows. Step was Vdeo Extracto (the vdeo was extracted to obta frames of the vdeo). Suppose (l, l,..., l m ) s a seres of movg mages, the some frames wth the N umber of frames of the total m of frames s selected, symbolzed by (f, f, f 3,... f ). Step was to obta the frames of the average vdeo frame extract results. f (x, y) represets the pxel value of -th frame wth = 0,,,.... The, the average value per pxel was take usg equato. The selected frame ca be ay frame or frame based o the desred terval. () (Advace ole publcato: 7 November 08)

4 IAENG Iteratoal Joural of Computer Scece, 45:4, IJCS_45_4_05 C. Backgroud Subtracto The backgroud subtracto process was used to detect movg objects o the vdeo [7]. I a study of sperm fertlty, the sperm that wll evetually fertlze the egg s the sperm that keeps movg [8]. Therefore, the backgroud subtracto process s ecessary for detectg movg sperm. I the case of sperm detecto, the advatages of dog the backgroud subtracto process are that the data used has of umodal characterstcs, the dstace betwee frames s short, ad the effect of lght chages s abset [9]. O the other had, the challege faced s the presece of backgroud objects that move ad the exstece of ew objects cosdered as backgroud. The put of the backgroud subtracto process was the preprocessed vdeo frames, ad the output were bary mages that represeted the objects (sperm) movg the vdeo. I ths research, the Frame Dfferece backgroud subtracto algorthm was appled [0]. I ths algorthm, the backgroud model was take from the frame (f) a momet before the curret frame. The equatos used to model the backgroud (B) mage o the Frame Dfferece algorthm was defed by []: B = f t () Foregroud (F) mage was obtaed by calculatg the dfferece betwee the backgroud mage value wth the curret frame: F = f t B (3) Ths algorthm was able to detect pxels that move quckly ad precsely but would fal to recogze f the movg object stopped stataeously D. Otsu Thresholdg At ths stage, a segmetato process was performed to dstgush or separate the detected object agast ts backgroud as a result of segmetato the form of bary mages. Iput for ths process was the mage extracted frames from the vdeo ad average frame result of the TABI (tme-averaged backgroud mage) procedure []. Furthermore, a BS process wth dfferet frame method was performed, resultg the dfferece the pxel value of ts correspodg coordates for all pxels. The, ths stage was followed by a thresholdg process usg the Otsu threshold method [3], where the dfferece value was less tha the threshold value. Thus, the color values were chaged to 0. If the value was greater tha or equal to the threshold value, the the color value was chaged to, as the followg equato [4]: 0 g( a, b) =, f ( a, b) < T, f ( a, b) T wth: g ( a, b) = Pxel mage values from thresholdg, whch cotas 0 or T = Threshold value Thus, bary magery would be obtaed as a referece (4) pot maxmzg cotrast for maxmum backgroud ad foregroud dfferetato. E. Morphologcal Flterg Features of the obtaed mage from the segmetato process usually stll cotaed ose, due to uwated objects beg segmeted. The morphologcal flterg method was used to elmate the ose [5]. The frst process was to remove objects that had less tha 400 pxels, thus reta objects that had more tha 400 pxels. The secod process was to make the object smoother by closg the small gaps of the objects. Ths process used mage morphology operato techques, where the edges of the mages obtaed stll eeded to smootheed usg the closg method. Closg s a morphologcal operato that ca be categorzed as a secod-level operato, meag that the closg s defed as a dlato operato, followed by eroso operato. The closg operato teds to refe the object o the mage by coectg fragmets ad elmatg small holes the object. F. Labelg Objects ad Calculatg the Coordate Pots of Objects Ceters After the flterg process mproved the mage, the mage was the searched for boudares usg the boudary detecto method [6]. Each of the foud objects was also labeled. From each object foud, the cetral pot coordates of each such object (x b, y b ) were searched usg equato 5. x b = A x A b = y A y (5) Wth: A beg the pxel area at pot (x, y ) beg the umber of pxels I ths research, the area of A pxel s ut, so equato 6 becomes: x y (6) xb = yb = G. Spermatozoa Trajectory Lear Regresso The process of trackg spermatozoa for oe sequece a statc vew space would result two-dmesoal posto values of motlty represetato. To be able to determe the shape of spermatozoa motlty, a test le take from lear regresso [7] of a set of spermatozoa posto values was requred. b = A y = a + bx (7) x y x x x y (8) (Advace ole publcato: 7 November 08)

5 IAENG Iteratoal Joural of Computer Scece, 45:4, IJCS_45_4_05 a y b = Wth beg the amout of data, x beg the x-axs posto, y beg the y-axs posto. The lear regresso le y = a + bx passes through a set of motlty spermatozoa posto values, whch measure the dstace to sperm motlty posto for oe sequece. H. Root Mea Sequece The RMS value should be sought to determe whether the mea sperm motlty s the straght le, whch compares the predcto value (lear regresso le) ad motlty posto of a spermatozoo durg oe sequece. If gve a set of data of,.e., {X, X,..., X }, the the RMS value woud be [8]: RMS = x r (9) (0) To calculate the dstace value r betwee pot Q (s, z) wth le Gx + Hy + J = 0 the followg equato s used Gs + Hz + J r = (5) G + H III. EXPERIMENTAL RESULTS The testg of spermatozoa vdeo movemet trackg ths research used two kds of data: vdeo recordg of huma spermatozoa from the UNSW embryology collecto ad vdeo of huma spermatozoa motlty/movemet selfrecorded from the sperm of some voluteers. I the spermatozoa recordg process, sperm samples were dropped o object glasses wthout cover glasses, the each was placed uder the objectve les, ad the hgh-speed camera was coected to the laptop usg a USB 3.0 cable coecto, actg as a replacemet for the ocular les. A. Acqusto of Test Data wth: The test data were used to vew trackg performace. The RMS = average value of spermatozoa dstace to the lear test data questo were the vdeo of huma spermatozoa regresso le motlty obtaed from the UNSW Embryology collecto r = spermatozoa posto dstace from the lear regresso (Fg. 4). The vdeo featured the ormal huma spermatozoa le motlty ad ts respose to progesteroe photo-release. = total data. Fg 4. The frame of moto vdeo motlty spermatozoa collecto UNSW Embryology Fg 3. Illustrato of determato of the dstace betwee pot ad le equato Fg. 3 shows the llustrato for calculatg the value of r, whch s the dstace betwee pot Q(s, z) ad a le equato. The followg equato s used to obta the equato of le Gx + Hy + J = 0: Gx + Hy + J = 0 () G = h k h k () H = J = h h k h k h k (3) (4) B. Huma Spermatozoa Data Acqusto The recordg of huma spermatozoa motlty was prepared by varyg the vscosty, objectve les magfcato, ad recordg frame rate (fps) beg performed to observe the best results of traceable spermatozoa. The speed of sperm moto reachg 35 µm/s ca be approprately captured by the camera whe set at 60 fps. Although the camera's frame rate capablty for recordg ca reach 0 fps, the specfcato of the computer devce was oly able to process 60 fps. Fg. 5.a shows the feld of vew of the system recorded through the camera after 0 mutes from sperm flud ejaculato wth 0x objectve les magfcato. It ca be see spermatozoa populato were ot able to move aturally because t ecoutered obstacles ts path ( the form of other spermatozoa or other objects). Also, the szes of vsble sperm cells were ty, makg t dffcult to coduct observatos. (Advace ole publcato: 7 November 08)

6 IAENG Iteratoal Joural of Computer Scece, 45:4, IJCS_45_4_05 Fg. 5. a. Frames of spermatozoa motlty vdeo 0 mutes after ejaculato, 0x objectve les magfcato (b) 40x objectve les magfcato(c) 00x objectve les magfcato ad (d) Frames of spermatozoa motlty vdeo 30 mutes after ejaculato, 40x objectve les magfcato Fg. 5.b shows the feld of vew of the system recorded through the camera after 0 mutes from sperm flud ejaculato wth 40x objectve les magfcato. It ca be see that the spermatozoa populato were stll ot able to move aturally because t ecoutered obstacles ts path ( the form of other spermatozoa or other objects). Also, the szes ad shapes of vsble sperm cells could be clearly observed. I Fg. 5.c, the camera was less focused, so the sperm morphology was less evdet. The head to tal shapes could ot be adequately recogzed. The recordg of the mage used 00x objectve les magfcato. Wth the durato of strrg at room temperature for 30 mutes after the sperm flud was ejaculated, observatos were made usg a mcroscope wth 40x objectve les magfcato. From ths observato, the sperm morphology ad motlty could be see clearly. The shape of the head ad tal, as well as the movemet of sperm, could be observed well, as Fg. 5.d. C. Test O Sperm Idetfcato Process Ths expermet was performed o spermatozoa vdeo data after 30 m of leavg wth a 40x objectve les. The spermatozoa vdeo was a vdeo wth pxel resoluto wthout vdeo compresso AVI format. Ths vdeo represets the actual sperm motlty codto ad has 0 frames. I Fg. 6, (a) s the frame of the vdeo wth (a) beg the 5th frame mage, (a) beg the 45th frame, ad (a3) beg the 05-th frame. (b) s the result of the backgroud recostructo by takg 50 frames out from a total of 0 frames; the frame was selected wth the -frame terval betwee frames. (b) s the result of the detecto ad segmetato of the vehcle movemet, where (b) correspods to the 5th frame, (b3) correspods to the 45th frame, ad (b4) correspods to the 05th frame. Image (c) s the result of backgroud recostructo by takg 00 frames wth ter-frame tervals of frame. Image (d) s the result of backgroud recostructo by takg all frames,.e., 00 frames. The results of the backgroud ad ts relato to the frames the vdeo are show the order as Fgure 6. Fg. 6 The motlty mages of spermatozoa: (a) s the orgal vdeo extracted mage, where (a) s the 5th frame mage, (a) s the 45th frame ad (a3) s the 05th frame. Fgures (b) ad (c) are the resultg backgroud mages from recostructo From Fg. 5, t ca be see that the umber of frames volved the backgroud recostructo process does ot sgfcatly affect the backgroud results obtaed. The backgroud results obtaed used oly 50 frames or 4.7% of all frames, resultg a backgroud smlar to the recostructo usg 87.5% of all frames. D. Results of Spermatozoa Trackg Test Trackg was doe o two kds of data, amely huma sperm data ad test data. Test data was a deal vdeo for motorg usg the Frame Dfferece Backgroud Subtracto ad Mathematcal Morphology. The vdeo had good cotrast, suffcet amout of spermatozoa, ad o mpurtes. Trackg o test data amed to test the methods used before beg used huma sperm data. Fg 7. (a) Image of the 0th vdeo frame of the test data, (b) Bary mage of the 0th vdeo frame of test data after the process, (c) Trackg of the 0th frame of test data spermatozoa vdeo The huma spermatozoa motlty test data has a durato of approxmately 3 secods wth dmesos of 5 x 5. Ths vdeo s deal for testg because spermatozoa stad out wth hgh cotrast ad o mpurtes. There were varous motltes of spermatozoa the feld of vew, such as lear, stoppg ad the bedg, bumpg, ad colldg. The, ths vdeo was cut to 0 frames oly wth durato of 4 secods. (Advace ole publcato: 7 November 08)

7 IAENG Iteratoal Joural of Computer Scece, 45:4, IJCS_45_4_05 After backgroud subtracto, thresholdg, ad morphology operatos, we obtaed a bary mage as Fg. 7.b, whch s a bary mage captured from the 0th frame. The spermatozoa trackg process ca be performed for all vsble objects the feld of vew, whch was doe from oe frame to the ext. I Fg. 7.c., sperm trackg appeared o the 0th frame E. Results of Huma Spermatozoa Vdeo Trackg The huma spermatozoa motlty test data had a durato of approxmately secods wth dmesos of 80 x 960. The spermatozoa vdeo data was obtaed after 30 mutes of cubato wth a 40x objectve les. As the test data, ths vdeo the backgroud subtracto, thresholdg, ad morphology operato processes were coducted, whch produced a bary mage as show Fg. 8.a., dsplayg the bary mage obtaed from the 0th frame. Fg 8. (a) The 0th frame of the huma sperm vdeo, (b) Bary mage of the 0th frame of the huma sperm vdeo, (c) Trackg of the 0th frame of huma sperm vdeo The movemet of the marker represets the sperm motlty trackg durg the durato of the vdeo observato. The ceter posto of ths marker was recorded regardg x posto ad y posto, the the lear regresso ad RMS were calculated. The motlty of the spermatozoa durg the 0 frames was revewed wthout colldg obstacles the form of mpurtes. Thus, the trackg performed was the atural movemet of spermatozoa ad produced a path form that ca be searched for ts lear regresso value, ad ts root meas square from the motlty path of spermatozoa. The ext process was to determe the lear regresso for each spermatozoo usg equatos (7), (8), ad (9). The lear regresso equato for spermatozoa was show Table 3. TABLE POSITIONS OF TEST SPERMATOZOA DURING TRACKING Sperm- Sperm- Sperm-3 Sperm-8 Frame To x y x y x y x y TABLE POSITIONS OF HUMAN SPERMATOZOA DURING TRACKING H-Sperm H-Sperm H-Sperm3 H-Sperm4 Frame To x y x y x y x y F. Lear Regresso Calculato Aalyss The posto varables recorded durg the sperm moto trackg motlty were the depctos of the path forms. The RMS value was determed from the spermatozoa posto durg the durato of the observatoal vdeo o ts straght le. The more spermatozoa posto that led from the drect le, the RMS value would be hgher. From here, the threshold value that dstgushes spermatozoa wth straght or bet paths was obtaed. From the spermatozoa trackg process, usg both huma sperm data ad test data, the spermatozoa motlty posto values were obtaed durg the observatos the x-axs ad y-axs coordates show Table ad Table. Where m both tables are the umber of frames per sperm, wth the umber of sperm test data are 8 ad the umber of huma sperm data are 4. The umber of frames for each sperm s dfferet depedg o the vdeo of sperm movemet per frame. From the table of the spermatozoa posto motlty, the researchers obtaed a plot that descrbes the shapes of the paths of spermatozoa as Fg. 9 ad Fg.0. Fg 9. The plot of test data spermatozoa Fg 0. The plot of huma spermatozoa motlty (Advace ole publcato: 7 November 08)

8 IAENG Iteratoal Joural of Computer Scece, 45:4, IJCS_45_4_05 G. RMS Calculato After obtag a lear regresso value for each spermatozoo, the ext step was to fd the RMS value represetg the average dstace betwee the spermatozoa posto value ad the lear regresso le. From ths RMS value, t would seem that f the posto of spermatozoa that was far from the regresso le added up, the the RMS value would be hgher. The RMS value would gve a average pcture of the spermatozoa posto durg ts motlty, whch would determe whether the locato of the movemet was far from the straght le or ot. The RMS value was calculated usg equato (9) ad (0). The RMS value of each spermatozoo could be see Table 3 ad Table 4. TABLE 3 LINEAR REGRESSION AND RMS FOR EACH TEST DATA SPERMATOZOON Order of Sperm Lear Regresso RMSValue y = 0,3 x + 34,8,4 y =,09 x - 3,4 8,68 3 y= 0,40 x + 87,5 3,90 4 y = 0,6 x + 86,7,43 5 y= -0,93 x + 45, 77,03 6 y = -,39 x + 599,3 3,9 7 y = 3,56 x - 30,0 6,75 8 y= -4,80 x + 686,0 63,56 TABLE 4 LINEAR REGRESSION AND RMS FOR EACH HUMAN SPERMATOZOON Order of Sperm Lear Regresso RMSValue y = 5,77 + 0,33 x,03 y = 9,97 + 0,6 x 4,9 3 y =,68 + 0,39 x 6,96 4 y = -3,95 + 0,98 x 9,7 5 y = -54,75 +,06 x 5,68 6 y = 908,85 -,4 x 6,46 7 y = 54, - 0,4 x 4,6 8 y = 54,4-0,7 x 7,5 9 y = 33,66 -,00 x 7,74 0 y = 36,3 + 0,6 x,64 y = 90,7 + 0,09 x 4,39 y = 689,6-0,69 x 0,78 3 y = -,9 + 0,77 x 6,74 4 y = 07,35 + 0,3 x 0,86 By comparg the plot of the spermatozoa posto to the RMS value, t ca be cocluded that the RMS threshold value for the spermatozoa path s 0. Progressve spermatozoa that move straghtforward or forward but ot straght, sometmes twsted, ad slow movemet has RMS value below 0. Whle spermatozoa oprogressve whose tal rus, but t does ot move forward, sometmes t appears to be spg or just rug place has a RMS value above 0. Based o the value of the threshold the for the test data, there are four progressve spermatozoa ad four o-progressve spermatozoa, whle for huma spermatozoa data there are te progressve spermatozoa ad four oprogressve spermatozoa. Table 5 shows the umber ad percetage of the spermatozoa group. TABLE 5 NUMBER AND PERCENTAGE OF SPERMATOZOA GROUP Types of sperm data Test Data H-Sperm Groups Prog. No-Prog. Prog. No-Prog Number Percetage 50% 50% 7% 9% Note: Prog = Progressve Of the 8 tested spermatozoa tested data, there were 50% progressve ad 50% oprogressve. As for 4 huma spermatozoa trackg, there were 7% progressve ad 9% oprogressve IV. CONCLUSION Wth the devce beg developed, the determato of huma moto spermatozoa abormaltes vdeo fles ca be doe. The path shape detfes the posto of the spermatozoa movemet of the trackg results based o the average dstace of ts posto o the lear regresso le. Wth threshold te there are four progressve spermatozoa ad four o-progressve spermatozoa for the test data, whle for huma spermatozoa data there are te progressve spermatozoa ad four o-progressve spermatozoa. The methods used successfully determe 8 (eght) spermatozoa data UNSW Embryology, ad 4 huma spermatozoa. Of the eght tested spermatozoa tested data, there were 50% progressve ad 50% o-progressve. As for the 4 matraed spermatozoa, there were 7% progressve ad 9% o-progressve. Accordg to the WHO laboratory maual for the examato ad processg of huma cemet 00, a value of 7% progressve meas the movemet of ormal huma spermatozoa. The offered system algorthms were perceved to be represetatve for sperm calculato, although there was sperm traffcs durg observato. REFERENCES [] S. A. Rothma ad A. A. Reese, Seme Aalyss: The Test Techs Love To Hate, Medcal Laboratory Observer, vol. 39, o. 4, pp. 8 0, 007. [] P. Hdayatullah, T. Megko, ad R. Mur, A survey o multsperm trackg for sperm motlty measuremet, Iteratoal Joural of Mache Learg ad Computg, vol. 7, pp. 44 5, 07. [3] J. Ya z, C. Soler, ad P. Satolara, Computer asssted sperm morphometry mammals: a revew, Amal reproducto scece, vol. 56, pp., 05. [4] D. T. Stephes, R. Hckma, ad D. D. Hosks, Descrpto, valdato, ad performace characterstcs of a ew computerautomated sperm motlty aalyss system, Bology of reproducto, vol. 38, o. 3, pp , 988. [5] S. Youg, W. Tzeg, Y. Kuo, M. Hsao, ad S. Chag, Real-tme tracg of spermatozoa: A system for mproved evaluato of sperm progresso, IEEE egeerg medce ad bology magaze, vol. 5, o. 6, pp. 7 0, 996. [6] A. Tambol ad L. Volkert, Computer aded mage aalyss of moble mcroscopc objects: the detecto phase, Boegeerg Coferece, 003 IEEE 9th Aual, Proceedgs of. IEEE, 003, pp [7] Q. L, X. Che, H. Zhag, L. Y, S. Che, T. Wag, S. L, X. Lu, X. Zhag, ad R. Zhag, Automatc huma spermatozoa detecto mcroscopc vdeo streams based o ope cv, Proceedgs 5th Iteratoal Coferece o Bomedcal Egeerg ad Iformatcs (BMEI). IEEE, 0, pp (Advace ole publcato: 7 November 08)

9 IAENG Iteratoal Joural of Computer Scece, 45:4, IJCS_45_4_05 [8] [9] [0] [] [] [3] [4] [5] [6] [7] [8] [9] [0] [] [] [3] [4] [5] [6] [7] [8] J. L, K. K. Tseg, H. Dog, Y. L, M. Zhao, ad M. Dg, Huma sperm health dagoss wth prcpal compoet aalyss ad kearest eghbour algorthm, Proceedgs Iteratoal Coferece o Medcal Bometrcs (ICMB). IEEE, 04, pp M. R. Ravafar ad M. H. Morad, Low cotrast sperm detecto ad trackg by watershed algorthm ad partcle flter, Proceedgs 8th Iraa Coferece o Bo-Medcal Egeerg. IEEE, 0, pp V. Khryashchev, L. Shmaglt, M. Golubev, ad A. Shemyakov, The developmet of object trackg ad recogto algorthms for au- dece aalyss system, IAENG Iteratoal Joural of Computer Scece, vol. 40, o., pp , 03. W. H. Orgazato, WHO Laboratory Maual for The Examato ad Processg of Huma Seme, 5th edto. Geeva: World Health Orgazato, 00. A. Sopharak, B. Uyyaovara, ad S. Barma, Automatc mcroaeurysm detecto from o-dlated dabetc retopathy retal mages usg mathematcal morphology methods, IAENG Iteratoal Joural of Computer Scece, vol. 38, o. 3, pp , 0. P. Korprobst, R. Derche, ad G. Aubert, Image sequece aalyss va partal dfferetal equatos, Joural of Mathematcal Imagg ad Vso, vol., o., pp. 5 6, 999. W. Log ad Y.-H. Yag, Statoary backgroud geerato: A alteratve to the dfferece of two mages, Patter recogto, vol. 3, o., pp , 990. B. Gloyer, H. K. Aghaja, K.-Y. Su, ad T. Kalath, Vdeo-Based Freeway Motorg System Usg Recursve Vehcle Trackg, I Proc. of IS & T-SPIE Symposum o Electroc Imagg: Image ad Vdeo Processg, Volume 4, 995, pp A. Djurayev ad G. Prmora, Automatc terestg object extracto from mages based o edge formato ad texture aalyss, Itera- toal Joural of Scetfc ad Research Publcatos, vol. 6, o., pp , 990. I. G. S. Masdyasa, I. D. G. H. Wsaa, I. K. E. Purama, ad M. H. Purama, Modfed backgroud subtracto statstc models for mprovemet detecto ad coutg of actve spermatozoa motlty, Lotar Komputer Joural, vol. 9, o., pp. 8 39, Aprl 08. E.Borges Jr, A. Sett, D. Braga, R. Fguera, ad A. Iacoell Jr, Total motle sperm cout has a superor predctve value over the who 00 cut-off values for the outcomes of tracytoplasmc sperm jecto cycles, Adrology Joural, vol. 4, o. 5, pp , 06. H. B. Basoek, A. D. Wbawa, ad I. K. E. Purama, Improvg sperms detecto ad coutg usg sgle Gaussa backgroud subtracto, Iteratoal Semar o Applcato for Techology of Iformato ad Commucato (ISematc). IEEE, 06, pp H. Y, Y. Cha, S. X. Yag, ad X. Yag, Fast-movg target trackg based o mea shft ad frame-dfferece methods, Joural of Systems Egeerg ad Electrocs, vol., o. 4, pp , 0. Y. Zhag, X. Wag, ad B. Qu, Three-frame dfferece algorthm research based o mathematcal morphology, Proceda Egeerg, vol. 9, pp , 0. A. A. Karm, A proposed backgroud modellg algorthm for movg object detecto usg statstcal measures, Iraq Joural of Scece, vol. 58, o. 3A, pp. 8 89, 07. N. Otsu, A threshold selecto method from gray-level hstograms, IEEE trasactos o systems, ma, ad cyberetcs, vol. 9, o., pp. 6 66, 979. D. S. Alex ad A. Wah, Backgroud subtracto frame dfferece algorthm for movg object detecto ad extracto, Joural of Theoretcal ad Appled Iformato Techology, vol. 60, o. 3, pp , February 04. B. Grod, Dgtal Image processg EE-368/CS-3. Departmet of Electrcal Egeerg Staford Uversty, 03. G. I. Rathod ad D. A. Nkam, A algorthm for shot boudary detecto ad key frame extracto usg hstogram dfferece, Iteratoal Joural of Emergg Techology ad Advaced Egeerg, vol. 3, o. 8, pp , 03. J. T. Lals, A ew multclass classfcato method for objects wth geometrc attrbutes usg smple lear regresso, IAENG Iteratoal Joural of Computer Scece, vol. 43, o., pp , 06. I. Kufareva ad R. Abagya, Methods of prote structure comparso, Homology Modelg. Sprger, 0, pp I Gede Susrama Masdyasa has receved hs M.T. from Isttut Tekolog Sepuluh November (ITS) Surabaya. He also has got hs S.T. from Electroc Egeerg Departmet of Isttut Tekolog Adh Tama Surabaya (ITATS). Curretly He s a Doctor Caddate Electroc Egeerg ITS Surabaya uder supervo of Prof. DR. IR. Maurdy Her Puromo ad DR. I Ketut Eddy Purama, ST. MT. I Ketut Eddy Purama receved the bachelor degree Electrcal Egeerg from Isttut Tekolog Sepuluh Nopember (ITS), Surabaya, Idoesa 994. He receved hs Master of Techology from Isttut Tekolog Badug, Badug, Idoesa 999. He receved Ph.D degree from Uversty of Groge, the Nederlads 007. Curretly, he s the staff of Electrcal Egeerg Deparmet of Isttut Tekolog Sepuluh Nopember, Surabaya, Idoesa. Hs research terest s Data Mg, Medcal Image Processg ad Itellget System Maurdh Hery Puromo receved the bachelor degree from Isttut Tekolog Sepuluh Nopember (ITS), Surabaya, Idoesa 985. He receved hs M.Eg., ad Ph.D degrees from Osaka Cty Uversty, Osaka, Japa 995, ad 997, respectvely. He has joed ITS 985 ad has bee a Professor sce 003. Hs curret terests clude tellget system applcatos, mage processg, medcal magg, cotrol ad maagemet. He s a Member of IEEE ad INNS (Advace ole publcato: 7 November 08)