Algorithm Research on Moving Object Detection of Surveillance Video Sequence *

Transcription

1 Opcs and Phooncs Journal do:0.436/opj.03.3b07 Publshed Onlne June 03 (hp:// Algorhm Research on Movng Objec Deecon of Survellance Vdeo Sequence * Kuhe Yang Zhmng Ca Lnglng Zhao Insue of Informaon Scence and Engneerng Hebe Unversy of Scence and Technology Shjazhuang05008 Chna Emal: yanguhe@6.com jczmdeveloper@gmal.com Receved 03 ABSTRACT In vdeo survellance here are many nerference facors such as arge changes complex scenes and arge deformaon n he movng objec racng. In order o resolve hs ssue based on he comparave analyss of several common movng objec deecon mehods a movng objec deecon and recognon algorhm combned frame dfference wh bacground subracon s presened n hs paper. In he algorhm we frs calculae he average of he values of he gray of he connuous mul-frame mage n he dynamc mage and hen ge bacground mage obaned by he sascal average of he connuous mage sequence ha s he connuous nercepon of he N-frame mages are summed and fnd he average. In hs case wegh of objec nformaon has been ncreasng and also resrans he sac bacground. Evenually he moon deecon mage conans boh he arge conour and more arge nformaon of he arge conour pon from he bacground mage so as o acheve separang he movng arge from he mage. The smulaon resuls show he effecveness of he proposed algorhm. Keywords: Vdeo Survellance; Movng Objec; Deecon; Frame Dfference; Bacground Subracon. Inroducon Compared wh he relave sac mage he movemen mage conans more nformaon and we can exrac he conaned nformaon from he movemen mage by means of mage processng. The purpose of movng objec deecon s o exrac he requred nformaon from he mage. Consderng he complexy of he envronmen durng he mage acquson process he qualy of movng objec deecon depends on he followng characerscs: ably o adap o changes n amben lgh ably o adap o manan good resuls n a varey of weaher condons ably o avod nerference from deecng smlar flucuaons and jer exss n he scene ably o accuraely denfy he errac movemen of large areas and he change of he objec s quany n he movemen scene. The paper frs nroduces he prncple of frame dfference and bacground subracon and hen researched he common wo-frame dfference and hree-frame dfference [] lasly pu forward a bacground subracon based on codeboo model and Bayesan classfcaon. * Foundaon Iem: Ths wor was suppored by he Technologcal Innovaon Funds of Hebe Unversy of Scence and Technology (NO. 03). Frame Dfference.. The Prncple of Frame Dfference The frame dfference s he mos effecve mehod for deecng change of wo adjacen frames n he vdeo mage []. Suppose he vdeo frame a me s gven by f ( xy ) hen he nex frame a + s f( x y ). The bnary mage operaon resuls of frame dfference can be defned as: f ( xy ) f( xy ) Th Dxy ( ) 0 oherwse where Th represens he hreshold for decson. If he frame dfference mage value s greaer han he hreshold hen pu he pon as a foreground pxel. Smlarly when less han he hreshold regardng he pon as a bacground pxel... Two Neghbour Frames Dfference () Frsly calculae he dfference of wo adjacen frame mages hen ge mage resul D ( x y ): D f f 3 () where f (xy) and f - (xy) respecvely represen he wo adjacen frame mages D (xy) represens dfference m- Copyrgh 03 ScRes.

2 K. H. YANG ET AL. 309 age. The so-called adjacen frame dfference s he case when se = and can be defned as: 0 bacground D T R foreground D T where T represens he hreshold for bnarzaon processng. Accordng o he formular (3) D (xy) s bnarzed and processed by mahemacal morphology flerng. Then accordng o he connecvy of he calculaed resul R (xy) f he area of he conneced regon s greaer han he hreshold value he area s judge as he objec area o deermne he mnmum enclosng recangle [3]..3. Three-Frame Dfference Ths mehod s an mproved mehod based on wo-frame dfference. The mehod exrac hree consecuve frame mages from he vdeo sream and he dfference of hree frame mages s used o ge he conour of movng objec. Then hs mehod can be appled o remove effecs on bacground because of objec movemen so as o oban more precse objec conour [4-6] and s operaon process s expressed as follows: bacground f( xy ) f ( xy ) T b (4) foreground f( xy ) f ( xy ) T bacground f ( xy ) f( xy ) T b (5) foreground f ( xy ) f( xy ) T where f ( xy ) s he -h frame T and T are boh hresholds b and b are he bnarzaon of wo adjacen frames dfference. Then logc and operaon s done o b wh b and ge he dfference mage. The operaon process s gven as follows: bacground b b d foreground b ( x y) b ( x y) (6) 3. Bacground Subracon 3.. The Prncple of Bacground Subracon In movng objec deecon bacground subracon s a frequenly-used deecon mehod whch carres ou dfference calculaon by he curren mage and bacground mage o deec he area of he movng objec [7]. The algorhm can be descrbed as: Sep one: Frsly we need o calculae he absolue gray mage of he curren frame mage and he bacground mage: (3) d I B (7) Sep wo: By seng he hreshold Th we can oban he bnarzaon mage hereby exracng he movng objec regon from he mage: f d Th b (8) oherwse Sep hree: usng mahemacal morphology o fler he dfference mage and hen analyss communcang regon. And f he area of conneced regon s larger han a gven hreshold value ha s a movng objec. 3.. Bacground Subracon Based on Codeboo Model Ths objec deecon based on he codeboo model s based on vecor quanzaon and cluserng [8-9]. By usng he quanzaon and cluserng dea he changed pxel afer mage sequence analyss s classfed and he code word se n a pxel called codeboo. Buldng a codeboo for each pxel s he ey of movng objec deecon based on he codeboo mode. Based on Km algorhm [0] he paper desgn he moon deecon mehod based on he codeboo model and he basc seps nclude codeboo creang codeboo flerng codeboo updang foreground deecon and bacground updang. The color model for evaluang color dsoron and brghness dsoron s shown as: In hs process Frs we need o buld a codeboo for each pxel. Because he lengh of he codeboo for each pxel s no he same as he ohers so se C = c c...c L here c L represens he codeboo whch lengh s L. Codeboo consss of code c =...L. The componen of codeboo nclude RGB vecor v ( R G B) and 6-uple array aux I f p q here RGB represens he average of code s pxel value I and respecvely represen he average of brghness and varance of brghness for each code pxel and las we ge he resul I R G B of code s maxmum me nerval p and q are respecvely fr me and las me. Fgure s he model for evaluang color dsoron and brghness dsoron used n he algorhm. Consderng me npu pxel x = (RGB) and code c are gven here f s frequency hen he RGB vecor s v ( R G B ). Se θ s he angle of x beween x and v δ s he dsance of x beween x and v. x v cos x v x R G B (9) (0) v R G B () x v RRGG BB () Then color dsoron can be defned as: Copyrgh 03 ScRes.

3 30 K. H. YANG ET AL. Afer bacground model μ s goen s deeced by foreground o smply compare respecve pxel code o he presen pxel value and he curren frame. If we fnd machng code word hen he curren pxel should belong o he bacground; oherwse belongs o he foreground. Color dsoron and lumnance dsoron as s machng crera: colords( x c ) () m Fgure. The color model for evaluang color dsoron and brghness dsoron. colords( x v ) cos x (3) The brghness dsoron n he Km algorhm s rede- fned as: rue f I I brghness( I I ) (4) false oherwse If codeboo conans L codes a me hen RGB npu vecor expressed: x = (R G B ). Judge ha wheher x s mached wh c n accordance wh color dsoron and brghness smlary. colords( x c ) (5) brghness I I rue (6) ( ) where means hreshold of color dsoron. If he above wo formulas hold hen x s mached wh c and code s updaed as: v m fr R fg G fb B f f f aux ( ) I I ( ) ( I I ) f max{ q} p And new code s creaed as: V (7) (8) ( R G B ) (9) L aux I (0) L where Σ s a cusom larger varance. Afer creang codeboo le λ = max{λ(n-q+p-)} hen o ge he maxmum me nerval whch any code s no exs durng overall codeboo buld process. By seng he hreshold value λ bacground model afer flerng he codes ou of bacground wll be obaned as follows: { c C T} () where T s he hreshold whch may be he half of he number of vdeo frames. brghness I I (3) ( m m ) where ε s allowed consan hreshold value of he pre-se color dsoron. If he above wo formulas a he same me esablshed x maches he m-h code word and code word s updaed and s deermned ha he curren pxel s a bacground pxel; oherwse s deermned ha he curren pxel as a foreground pxel a he same me o creae a new code word o he codeboo. 4. Movng Objec Recognon Based on Improved Bacground Subracon How o ge a relavely deal bacground s one of he ey ssues of bacground subracon pons sysem and s need o consder how accuraely o updae bacground n response o a seres of confoundng facors such as he lgh changes. Under he case ha he bacground mage can be changed as he lgh changed accordngly and acheve a ceran accuracy of deecon under he premse of hs opc n vew of he srenghs and weanesses of bacground subracon and frame dfference mehod here we combne wo mehods so ha can play each of he characerscs of he arge recognon and mprove he effec of movng objec deecon. Therefore based on he bacground subracon and frame dfference mehod hs paper presens an mproved bacground esablshmen mehod based on mul-frame mages wh bacground subracon and hen average of he resuls. In he mehod we frs calculae he average of he values of he gray of he connuous mul-frame mage n he dynamc mage and hen ge bacground mage obaned by he sascal average of he connuous mage sequence ha s he connuous nercepon of he N-frame mages are summed and fnd he average. In hs case wegh of objec nformaon has been ncreasng and also resrans he sac bacground. Evenually he moon deecon mage conans boh he arge conour and more arge nformaon of he arge conour pon from he bacground mage so as o acheve separang he movng arge from he mage. The specfc seps are as follows: Sep one: n he sreamng vdeo acquson se each mage fve frames fler sequence mage meda ge rd of he mage random nose. Thus we reduce he com- Copyrgh 03 ScRes.

4 K. H. YANG ET AL. 3 plexy overcome nose nerference. And hese mages are respecvely he mared as: f 0 - f. Sep wo: o use frame dfference o wo-wo dfference wh frames around curren frame hen average he sum of dfference mage se he resul as bacground of curren frame denoed as f b (xy). Sep hree: f a pon gray value n he frame dfference mage s larger han or equal o he hreshold value se n advance o use he average of mage gray value nsead of he gray value of he mage here; oherwse we can use he value of las frame nsead of correspondng poson. The equaon s expressed as: f f( xy ) f ( xy ) Th fb (4) mean f( xy ) f ( xy ) Th where mean denoes he average of mage gray value Th denoes he hreshold se n advance hereby ge bacground mage f b (xy). Sep four: o exrac he bacground mage B (xy) from he vdeo mage sequence so ha only nclude he saonary bacground mage. The curren frames f (xy) and f b (xy) are respecvely dfference wh he bacground mage B (xy)hen ge he resuls FD(xy) and FG(xy): f( xy ) B( xy ) T FD (5) f( xy ) B( xy ) T fb( xy ) B( xy ) T FG (6) fb( xy ) B( xy ) T where T s he hreshold se n advance. Sep fve: o ge he movng objec area mage by calculang nersecon of he dfference FD(xy) and FG(xy) hen use Mahemacal morphology o process moon regon and exclude he nerference of bacground nose. The gradaon of he bacground n he proposed mehod s closer o he real vdeo of he bacground hereby reducng he nerfuson degree of movng objec n he bacground. In addon because he vdeo sequence should be changed mage we need IIR fler [] o updae bacground. The IIR flerng mehod s relavely common. In hs mehod he curren frame mage s represened by F(xy) and he bacground mage s represened by B(xy) so he IIR fler updang mehod s expressed as follows: B ( ) B F (7) And n he prelmnary sage of bacground esmaon we frs selec an nal bacground and hen s updaed by he followng formula: B () B() ( M() ( M())) (8) ( C ( ) B ( )) where B () ndcaes he value of curren bacground mage and s B + () he updaed value. And C () s he value of curren frame and are boh coeffcens of updang. M () s expressed as: f ( C( ) B( ) Tb) M () oherwse (9) Because he presence of bacground nose f C () B () T b holds he curren mage s used as bacground; oherwse s used as foreground. Use dfferen updae coeffcens and o updae he curren mage bacground or foreground. If he curren mage belongs o bacground s used o updae; oherwse s used o updae. In addon consder he change of and wh me change we ge values () and () ; consder dfferen mage areas and parameers ( xy ) and ( xy ) are obaned where s he me coordnae x and y denoe he coordnaes of pxel n he mage. We combne bacground model updang wh prevous movng objec deecon resuls and se larger updae rae = 0. for he relavely pon of bacground. Whle he movng objec nformaon of foreground uses a smaller updae rae = 0.0. Afer mproved he nfluence of movng arge o bacground model s obvous reduced a he same me can be a mely and effecve response o he bacground change. 5. Expermenal Resuls and Analyss In hs paper expermens were conduced o basc bac- of n- ground subracon n expermenal envronmen door laboraory. Usng he fxed camera o real-me capure frames from vdeo hereby realzng movng objec recognon based on bacground subracon mehod. The expermenal resuls are shown n Fgure. Fgure shows he progressve realzaon of algorhm and ulmaely acheves he effec of objec deecon based on bacground subracon. Pcure a) s he bacground mage from vdeo; pcure b) s he dfference of curren frame and bacground mage; pcure c) s he effec of movng objec deecon. The expermenal resuls show ha he basc bacground subracon algorhm can only oban he conour of objec bu canno effecvely oban he full area of he objec. And Bacground model esablshed n he sac regon by hs mehod and realsc bacground have hgher smlary. However he bacground model and he rue bacground produce a devaon n he moon area. Because he mean resuls are affeced by he gradaon changes n he moon area herefore hs mehod s only applcable o he case wh fewer movng objecs and longer bacground. Because long me vdeo sequences s calculaed bacground updang should be slow down n order o ensure esmaon bas of he mnmum sequence mean. Copyrgh 03 ScRes.

5 3 K. H. YANG ET AL. and updae of he bacground model. Fnally expermens were conduced o he frame dfference mehod bacground subracon mehod and mproved mehod and he resuls were analyzed and compared. (a) bacground mage (b) he dfference of curren frame and bacground mage (c) he movng objec of deecon Fgure. The recognon process of bacground subracon. (fgure capon). 6. Conclusons Ths paper descrbed he movng objec deecon algo- provded an overvew of he rhms n vdeo survellance hree mehods for moon deecon ncludng frame dfference and bacground subracon mehod. Frsly frame dfference such as he common wo-frame dfference and hree-frame dfference s nroduced. Then bacground subracon based on codeboo and bayesan classfcaon s researched and analyzed. In hs paper based on bacground subracon we proposed an mproved bacground subracon mehod for deecng movng objec and descrbed n deal he esablshmen REFERENCES [] N. He Movng Objec Deecon and Shadow Removal Based on Vdeo Analyss maser s degree hess of Bejng Foresry Unversy 0. [] J. J. Du Research on Deecon and Tracng of Movng Objec n Inellgen Vdeo Survellance Sysem maser s degree hess of Souhwes Jaoong Unversy 009. [3] Y. Chen Research on Deecon and Tracng of Movng Objec n Inellgen Vdeo Survellance Sysem maser s degree hess of Jangsu Unversy 00. [4] F. Gao G. J. Jang H. X. An and M. S. Q A Fas Movng Objec Deecon Algorhm Journal of Hefe Unversy of Technology(Naural Scence) Vol. 0. [5] X. Jn Movng Targe Deecon Trac and Applcaon on Survellance Sysem Maser s Degree Thess of Zhejang Unversy 00. [6] Q. Wan Research on Mehods of Mulple Movng Objecs Deecng and Tracng n Inellgen Vsual Survellance Maser s Degree Thess of Hunan Unversy 009. [7] Y. Y. Wu and X. K. Yue Image Segmenaon for Space Targe Based-on Waershed Algorhm Compuer Smulaons Vol. 0 pp [8] X. J. Ren S. J. Xao and X. P. Peng Buldng Exracon from Remoe Sensng Image usng Improved Waershed Transform Compuer Applcaons and Sofware Vol. 8 No. 0 pp [9] J. M. Zhang J. Zhang and J. Wang Waershed Segmenaon Algorhm Based on Graden Modfcaon and Regon Mergng Journal of Compuer Applcaons Vol. 3 No. 0 pp do:0.374/sp.j [0] M. Y. Ren Sudy on Vdeo Movng Objec Segmenaon Based on Spao-Temporal Informaon Maser s Degree Thess of Unversy of Elecronc Scence and Technology of Chna 00. [] L. Lan Movng Targe Deecon and Tracng based on Frame Dfference Mehod and Image Bloc Machng Mehod Gude of Sc-Tech Magazne 0. Vol. 7 pp Copyrgh 03 ScRes.