Proceedgs of the 7th WSEAS It. Cof. o Sgal Processg, Computatoal Geometry & Artfcal Vso, Athes, Greece, August 4-6, 007 135 Realze a Moble Lae Detecto System based o Pocket PC Portable Devces P-Chh Hsueh, Chu-We Yeh, Chao-Ha Cheg, Pe-Yug Hsao 1, Mg-Jer Jeg ad La-Be Chag Departmet of Electroc Egeerg, 1 Departmet of Electrcal Egeerg Chag-Gug Uversty, 1 Natoal Uversty of Kaohsug 59, We-Hwa 1 Rd., Kue-Sha, Tao-Yua, Tawa Republc of Cha mjjeg@malhttp://www.cgu.edu.tw Abstract: - I ths paper, we preset a moble lae detecto system (LDS) based o the Pocket PC portable system. The Pocket PC applcato software wth geerc -D Gaussa smoothg flters whch are cludg the power-of-two appromato algorthm for the Gaussa coeffcets s easly to be hardware desg. I the lae detecto algorthm stage of a mage processg flow, the global edge detecto s able to trasfer the gray level mage to bary patter ad shows the edge of the object. The, usg ths bary patter fd out the traffc lae locato wth followg algorthm lke the peak-fdg ad groupg, edge coectg, lae segmet combato, lae boudares selecto. At last, the lae departure warg algorthm detects the vehcle whether traffc lae ad judges whether seds out the warg. Epermetal results both operated uder dfferet crcumstaces ad real mage sequeces wll also be preseted. Key-Words: - Moble lae detecto system, Pocket PC portable devces, Geerc -D smoothg flters, Lae detecto algorthm, Global edge detector, Lae departure warg algorthm. 1 Itroducto Traffc accdets have become oe of the most serous problems today s world. Most accdets occur due to drvers eglgece. May researchers ad vehcle makers are developg a drvg assstace system ad mprovg the drvg safety [1-14]. There are may research topcs o drver assstace systems maly focusg o the lae detecto techology sce t s basc ad has may applcatos, such as autoomous vehcles [1,4] ad the lae departure warg systems[5,8-14]. A mportat step developg a lae departure warg system s to have a robust lae detector. The lae detecto techque s oe of the most mportat parts the lae departure warg system. To realze the lae detecto, the ose dsturbace ca greatly affect lae dstcto. Nose sgals may be easly troduced to the orgal mage durg the mage acqusto stage, the mage compresso stage or eve the mage trasmsso stage [14]. To elmate such ose sgal ad esure the performace of mage, a addtoal step of ose reducto s requred. The ose reducto techques usually volve averagg the value of pels resde a local area ad geeratg a blurred or smoothed mage. Numerous software-based ad hardware-based edge detecto algorthms have bee proposed. Most algorthms are able to produce acceptable edge results, but fal as the ose sgal creases. Gaussa flter s oe of the specalzed weghted averagg flters. It has bee wdely adopted the feld of mage processg ad computer vso for years, ad s kow for ts mage smoothg ad ose reducto capablty. The Gaussa flter plays a mportat role dgtal mage processg tasks such as mage segmetato, mage blurrg, ad edge detecto. Such flter s usually adopted the fled of edge detecto. I ths paper, we preset a moble lae detecto system based o Pocket PC portable devce. The algorthm we used s dvded to two part, the frst part s mage preprocessg ad the secod part s lae detecto. To ehace portablty ad fleblty of the Lae departure warg systems, we wll develop a portable real-tme lae departure warg system should be cheap, easy to stall, ad able to be combed wth other vehcular cosumer devces, such as dgtal cameras, cell phoes, ad PDAs. Further, we are gog to dscuss our algorthm ad related research studes
Proceedgs of the 7th WSEAS It. Cof. o Sgal Processg, Computatoal Geometry & Artfcal Vso, Athes, Greece, August 4-6, 007 136 Geerc -D Gaussa smoothg flter ad lae detecto algorthm Frot level processg of the Lae Detecto system eed to use the lae detecto algorthm. For lae detecto algorthm applcatos, mage processg tasks are appled to the real-world mages. Nose sgals may be easly troduced to the orgal mage durg the mage acqusto stage, mage compresso stage or eve the mage trasmsso stage. To elmate such ose sgals, ad to esure the performace of the overall mage processg flow, a addtoal step of ose reducto s ecessarly requred. So we preset the Geerc -D Gaussa Smoothg Flter to reduce ose. The Gaussa flter s oe of the specalzed weghted averagg flters. It has bee wdely adopted the feld of mage processg ad computer vso for years, ad s kow for ts mage smoothg ad ose reducto capablty..1 Geerc -D Gaussa Smoothg Flter The values derved from the -D Gaussa dstrbuto are mostly comple floatg pot values, whch are dffcult to mplemet hardware. It would perform slowly eve f that certa hardware s mplemeted. The followg shows how we derve the orgal Gaussa smoothg mask. Defg the de (, of the ceter elemet of a 5 5 mask to be (0, 0), ad the whole mask to spa from (-, -) to (, ). The value of each elemet the 55 Gaussa smoothg mask s defed by Gaussa fucto. ( + y ) / G = e (1) Where, y = {-, -1, 0, 1, } ad =[0.1, 5.0]. The summato of the whole mask should be equal to 1 by the defto of Gaussa dstrbuto. Therefore, we eed to sum the whole 5 elemets ad ormalze them. S = = y= G G = G / S (3) To derve the dgtal-appromated -D Gaussa mask for hardware mplemetato, we use the combato of power-of-two terms to appromate each elemet, such that t ca be mplemeted by smply shft operatos hardware. The the tutve power-of-two appromato algorthm of () each of the 5 elemets may be wrtte as show Fg.1(a) after each elemet s determed, we stll eed to make sure that the sum would stll be close to 1. Let the value of each appromated coeffcet be deoted as A(,, ad aga the sum of twety fve curret appromated coeffcets would be S A = = y= A The power-of-two appromato for 1/S A s also determed usg the algorthm show Fg.1(a), ecept for that the rage of s eteded from 7 to 15. A eample of our dgtal-appromated Gaussa mask s show Fg.1(b). Appro(val) 1 term 0 rtterm[term] {0} 3 for 0 to 7 4 f term < λ (-) 5 the f val >= 6 the rtterm[term] (-) 7 val val - 8 term term + 1 9 retur rtterm (a) -3-6 ( + ) (b) 0-3 -3 + -4-3 0-3 - + -3-1 + -3 - + -3-3 -3 + -4-1 + -3 0 + -4-1 + -3-3 + -4-3 - + -3-1 + -3 - + -3-3 0-3 -3 + -4-3 0 Fg.1 Power-of-two appromato (a) Algorthm ad (b) Eample of the Gaussa mask for = 1.1 ad λ=. To descrbe the errors betwee the orgal Gaussa mask ad the -appromated Gaussa mask a formal way, we defe each of the appromated ormalzed elemets the -appromated Gaussa mask as: A = A / S (5) A Cosequetly, the absolute accumulated error s defed as: (4)
Proceedgs of the 7th WSEAS It. Cof. o Sgal Processg, Computatoal Geometry & Artfcal Vso, Athes, Greece, August 4-6, 007 137 E λ = = y= G A λ The decso for the acceptable accumulated error affects the algorthm. We adopt to appromate the Gaussa mask. Based o our emprcal epereces ad cost cosderato, we used the two-term s -appromato -D Gaussa mask as the proposed flter.. Global Edge Detecto The Global threshold edge detector uses a 3 3 mask to detect the dfferece betwee each pel. It eeds to obta mea value ad varace of ght pels to decde the edge pots. I order to mplemet by logc crcut, we modfed t as equato (8)-(9), whch has a very lttle dfferece betwee the orgal value ad the modfed oe. μ Δ = 1, Δy = 1 1 1, y = ( ) g ( + Δ, y + Δ 8 64 Δ = 1, Δy = 1 The we use the average dfferece of a 3 3 mask to replace the varace value of the orgal algorthm. 9 1 1, y = ( ) 8 64 = 1 δ μ Fally, we use the followg procedure to make pels value a 33 mask become bary. 1, δ, g ( + Δ, y + Δy ) = 0, δ y, y, y T < T After we modfed the orgal algorthm, we ca easly mplemet t by logc crcut. Furthermore, although Global threshold edge detector s a threshold value based algorthm, the cofgurato of Global threshold value, T, s much easer tha that of peak fdg based algorthm due to the sestve characterstc..3 Peak fdg ad groupg The processg frame wll become a bary mage after edge detecto procedure, the, the orgal peak fdg algorthm eed to be modfed. As show Fg., we have to defe three varables: Ps, Pe, Pp, where Star pot(ps) s the posto of frst clmbg up pot, Ed pot (Pe) s the posto of (6) (7) (8) (9) last clmbg dow pot, ad Peak pot (Pp) s the mddle pot betwee Ps ad Pe. After the edge detecto procedure, two sdes of lae mark may be detected. Therefore, we wll combe two close peak pot to a ew pot as show Fg.. After fdg peak pots the mage, we the group the peak pots, whch may locate at the same lae boudares. We use a 9 11mask to group peak, whch s show Fg.3. We make every peak pot to be the cetral pot of a 9 11 mask, ad let other pots the mask to be the same group lke as the cetral pot, ad the repeat the same operato aga ad aga. Fg. Peak pot ad combato of two ear peak pots. Fg.3 The groupg mask 9 11..4 Edge Coecto The selected peak pots are collected ad separated as may as le segmet by employg the least square method. Each produced le segmet s defed as below: L(P L (X L,Y L ),P U (X U,Y U ),b 0,b 1 ) Where P L s the top pot of le-segmet, P U s the bottom pot of le-segmet, b 0 s the tercept of le-segmet, ad b 1 s the slope of le-segmet. The b0 ad b1 are geerated by equato (11)-(1): b0 = X b1y b y = 1 = 1 = 1 1 = y ( y ) = 1 = 1 y (10) (11) (1)
Proceedgs of the 7th WSEAS It. Cof. o Sgal Processg, Computatoal Geometry & Artfcal Vso, Athes, Greece, August 4-6, 007 138 3. Archtecture of lae departure warg system I ths secto we eemplfy each state of the lae detecto algorthm result ad preset the software archtecture o our platform. The Lae detecto applcato archtecture shows Fg.4. The lower level of the software archtecture s portable hardware. Above hadhold hardware level s board support pocket lke bootloader, devce drvers, ad OEM Adaptato Layer. The termedate level s the kerel, devce maager, GEWS, ad servce maager of operato system. The, the mddle level betwee the applcato API ad lae departure warg applcato s a vrtual mache level. Fg.6 ehbts the traffc lae mage wth clear source ad t has bee processed each step of the algorthm. Whe the put mage s wthout ose addto, t ca clearly detect two traffc laes. Fg.7 presets the algorthm wthout Gaussa smoothg flter, the traffc lae wll be detected log th oe ad wrog ty le. That s ot eough to fd out whether the vehcles depart the traffc lae. Fg.8 shows the algorthm wth geerc -D Gaussa smoothg flter uder the groupg mask 9 11, the result shows both ma traffc laes whe vehcle s movg forward lke o ose addto case. Fg.9 show the lae detecto results dfferet processg mage ose effects. Fg.9(a) ehbts orgal traffc lae wthout ose addto. Fg.9(b) shows the traffc lae mage wth Gaussa ose addto by varace=0.01. Fg.9(c) shows the traffc lae mage wth geerc -D Gaussa smooth flter =0.9 ad groupg mask 9 11. The presetg algorthm ca capture two traffc les uder the put mage wthout ose addto whle the put mage wth Gaussa ose addto msses the correct traffc les. If we add Gaussa smoothg flter o mage processg frot level, the algorthm ca capture the correct traffc le o the both ma sdes. Fg.4 The archtecture of lae detecto applcato software bult o WCE moble OS. Fg.5 shows the traffc lae mage processg flow chart. The put mage s processed accordg to the followg order: geerc -D Gaussa smoothg flter, the global edge detecto, the peak-fdg ad groupg, the edge coectg, le segmet combato, lae boudares selecto, lae detecto ad dsplay results. (a) Orgal Image (b) Global Edge, T=10 (c) Peak Pots (d) Grouped Pots (e) Le Segmets (f) Lae Boudares Fg.6 Processg results for lae detecto step by step wth(v, V y ) = (150, 80) ad T=10. Fg.5 The traffc lae mage processg flow chart uses the lae detecto algorthm. The processg results wth dfferet codtos are show Fg.6, Fg.7 ad Fg.8, respectvely.
Proceedgs of the 7th WSEAS It. Cof. o Sgal Processg, Computatoal Geometry & Artfcal Vso, Athes, Greece, August 4-6, 007 139 processed by geerc -D Gaussa smoothg flter wth =0.9 ad the groupg mask 9 11. (a) Gaussa Nose Image Varace=0.01 (b) Global Edge,T=10 (c) Peak Pots Fg.10 shows the epermet platform ad the cocept drawg of the devce placemet. The devce ca be placed uder the frot wdsheld of vehcles. The platform s the Pocket PC electroc product from recet market wth Xscale 70 CPU. (d) Grouped Pots (e) Le Segmets (f) Lae Boudares Fg.7 Processg results for lae detecto flow ad each step mages wth Gaussa ose, mea=0, varace=0.01 ad the groupg mask 9 11. Fg.10 Result for lae detecto usg Pocket PC wth Xscale70 CPU as the platform (a)nose Image after Gaussa smoothg flter (b) Global Edge (c) Peak Pots (d) Grouped Pots (e) Le Segmets (f) Lae Boudares Fg.8 Processg result for lae detecto flow ad each step mages wth geerc Gaussa -D flter ad reszg the groupg mask to 9 11. 4. Cocluso I ths paper, we preset a detaled software hadheld lae detecto system based o the Pocket PC portable devce, whch ca be easly mouted o real vehcle ad dramatcally mprove safety. The software lae detecto algorthm ca process the calculato very fast ad easly set up o PDA devce from recet market. The proposed lae departure detecto algorthm let us to detect lae departure uder a hgh vehcle departure speed ad avod false alarm stuato successfully. At last, the evaluatos prove that ths system s robust most stuatos cludg Gaussa ose addto. Ackowledgemet Ths work was supported part by Natoal Scece Coucl, Tawa, ROC. Uder Grat NSC95-1-E-390-039 ad NSC94-15-E-18-010. Fg.9 Lae detecto results dfferet ose addto mages. (a) Orgal traffc lae Image. (b) The traffc lae mage wth Gaussa ose addto by varace=0.01. (c) The traffc lae mage Refereces:
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