Journal of Terrestrial Observation

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1 Journal of Terrestral Observaton Volume ssue 1 nter 010 Artcle 6 Automated Georeferencng of Hstorc Aeral Photograph Jae Sung Km Chrstopher C. Mller and James Bethel Coprght 010 The Purdue Unverst Press. All rghts reserved. SSN

2 Automated Georeferencng of Hstorc Aeral Photograph Jae Sung Km Chrstopher C. Mller and James Bethel Purdue Unverst ABSTRACT Hstorc aeral photos are tpcall ver popular sought-after collectons n lbrar archves. Ther ablt to be used n GS s lmted however b the laborous and panstakng georeferencng process. A method s presented for automatng the georeferencng of hstorc aeral photograph. n ths method the Harrs Corner Detector s used to detect corner ponts n alread-georeferenced and unreferenced aeral photos whch are then matched b cross correlaton. Falsel-matched corner ponts are removed wth the applcaton of the Random Sample Consensus wth a s parameter transformaton. The pel arras of nler corner pont pars are nput to a Java program developed wth ArcObjects whch converts ther pel coordnates to map coordnates. The unreferenced aeral photos are then rectfed and georeferenced b a arp functon wth a frst order polnomal opton. The results of tests thus far ndcate the method s satsfactor and promses to be an mportant component n an aeral photo lbrar dgtzaton workflow. KEYORDS Georeferencng; Harrs Corner Detector; Matchng; Cross Correlaton; RANSAC; ArcObjects 1. NTRODUCTON The ncreasng mportance of GS across dscplnes s placng addtonal emphass on the need to georeference useful analog materals that are often left to atroph n map collectons and lbrares. Tpcall georeferencng s a tme- and labor-ntensve process whereb users manuall determne n unreferenced data a seres of control ponts that can also be dentfed n referenced data. Ths s usuall performed n a desktop GS package and therefore requres sgnfcant process overhead. Ths paper presents an automated georeferencng methodolog that automates the appromate georeferencng of vertcal analog aeral photo eposures n areas of low relef to dgtal orthophotoquads. A consecutve applcaton of the Harrs Corner Detector Harrs and Stephens 1988 matchng b cross correlaton and Random Sample Consensus RANSAC dentfes nler control pont matches from lke mager and the resultng coordnate arra nforms a Java arp functon specfcall a frst-order polnomal or s-parameter transformaton n ArcObjects to The Journal of Terrestral Observaton Volume Number 1 nter

3 58 Jae Sung Km Chrstopher C. Mller and James Bethel The Journal of Terrestral Observaton Volume Number 1 nter 010 permanentl transform the unreferenced data n real coordnate space.. Methodolog.1. Harrs corner detector To georeference mages a geometrc relatonshp between mages must be establshed b dentfng correspondng ponts from both fles. One method of defnng a set of nterest ponts s to assume all corner ponts are canddates and smpl etract the most conspcuous corners based on ther hgher cornerness values. The Harrs corner detector algorthm Harrs and Stephens 1988 was developed based on the earler Moravec low-level corner detector Moravec 1980 mprovng upon the Moravec detector s ansotropc response nos response and senstvt to edges. The Harrs corner detector analzes gradents n a patch to provde cornerness measures for mage data Stottnger 008 and s descrbed b Derpans 007 as equaton 1 1 where s the mage functon and c s the auto-correlaton functon at a pont gven a shft. f 1 λ λ are the egenvalues of matr C n equaton there are three cases to be consdered. f both egenvalues are small t sgnfes a flat local auto correlaton and a constant ntenst mage wndow. A hgh value n one of the egenvalues and a low value n the other means an edge was detected. Two hgh egenvalues dentf a corner a requrement for ths approach. To locate corners an mage functon Harrs and Stephens 1988 was used as n equaton 3: [ ] [ ] [ ] [ ] + + C c ] [ ] [ + + c

4 Automated georeferencng of aeral photograph 59 R λ1λ k λ1 + λ det A k trace A R s postve n the corner regons negatve n the edge regons and small n the flat regon. Therefore we created mage functon R usng a threshold from the mamum R so that an approprate number of corners are detected. The constant k n equaton 3 ndcates a tunable parameter. n the Harrs functon 0 s the border between corner and edge Stottnger 008 and the values between 0.04 and 0.15 are known as feasble values for k. Once the corners are detected non-mamum suppresson was appled n order to reduce each corner n N-neghborhood to a sngle pel. To do ths an n b n mamum flter was created and compared to the corner mage and onl mamum values are etracted. 3.. Match b cross correlaton Accordng to Gonzalez et al. 004 the best match of w n f s the locaton of the mamum value n the resultng correlaton mage when we treat w as a spatal flter and compute the sum of products or a normalzed verson of t for each locaton of w n f. Therefore we created 101 b 101 pel wndows for each corner n the referenced mage computed the correlaton at each pont n the unreferenced mage and etracted mamum values n both drectons--from and to the unreferenced mage. The correlaton at a pont can be computed as equaton 4 c u v u u v v 1 [ u u v v ] 4.3. RANSAC for s-parameter transformaton RANSAC Random Sample Consensus Fschler and Bolles 1981 etracts onl nlers from samples b fttng data to a model wth the most nlers of all models generated randoml N tmes as n equaton 6. A s-parameter transformaton Mkhal et al. 001 such as equaton 5 was used as a model. X a0 + a1 + a 5 Y b0 + b1 + b where X Y s the coordnate n the referenced mage and s the coordnate n the unreferenced mage. RANSAC wth a s-parameter transformaton s eecuted n s steps: 1. Snce there are s unknown parameters a a a b b b we need s equatons to solve for the unknowns. Because one pont par gves two equatons we randoml select three ponts from matched pont samples. The Journal of Terrestral Observaton Volume Number 1 nter 010

5 60 Jae Sung Km Chrstopher C. Mller and James Bethel. Calculate s parameters a from randoml chosen pont pars. 3. Compute ever par of ponts n the second mage usng a s-parameter transformaton of the ponts n the frst mage. 4. Determne the sum of squared error between the estmated ponts and orgnal ponts n second mage. 5. f the error for each pont s less than the tunable threshold we used 30 square pels the ponts are nlers. Otherwse the are outlers. 6. Repeat steps 1-5 N tmes as n equaton 6 N log1 p log1 1 e s 6 where e s the probablt that a pont s an outler S s the number of ponts n a sample N s the number of teratons and p s the desred probablt n a good sample. The transformaton that produces the most nlers s the best model and the nlers are the correspondng ponts n both mages..4. ArcObjects wth JAVA ArcObjects s a sute of lbrares released b Envronmental Sstems Research nsttute ESR for software and tool development for ther ArcGS envronment. After pont pars are matched n both the referenced and unreferenced mages the unreferenced mage was rectfed and referenced b ArcObjects arp geoprocessor functon ESR 009. Because the coordnates of the matched ponts n each mage are nothng more than a par of pel nde values relatve to the edge of the mage the must be converted to some geographc coordnate sstem n order to be transferred from the referenced mage to the unreferenced. ArcObjects Raster class ncludes two methods.tomapx and.tomapy whch convert raster pel coordnates to map coordnates wthn some geographc coordnate reference sstem. These map coordnates are then called b the arp functon to transform the mage nto a full georeferenced dataset. For transformaton t was found out that the frst order polnomal lke equaton 7 suffced: X a Y b a + a + b + b where source and target coordnates X Y share the map s lnear unt. The Journal of Terrestral Observaton Volume Number 1 nter

6 Automated georeferencng of aeral photograph Applcaton and result Two earl tests ndcate the algorthm performs ver well. n both scanned unreferenced aeral photo eposures were referenced aganst georeferenced photos of the same area n some other near ear. Photos chosen for the tests ncluded 1963 and 1971 mages of the Purdue est Lafaette campus and 1939 and 1950 mages of the ashngton Street brdge area n Crawfordsvlle ndana. All mages were n tagged mage fle format tff. These frame mages were near vertcal wth terran relef a small fracton of the flng heght above ground. Table 1. Test datasets for automatc georeferencng Area Referenced Unreferenced Tme Gaps rs Purdue Campus 1971.tff 1963.tff 8 Crawfordsvlle 1939.tff 1950.tff 11 To start the test the 1971 Purdue campus and 1939 Crawfordsvlle photos were manuall georeferenced aganst 005 ndanamap Orthophotograph to be used as reference data for the 1963 and 1950 unreferenced mages respectvel. No attempt was made to reference mages 1963 and 1950 drectl aganst the 005 ndanamap Orthophotograph because man features on the earth surface are suspected to have been changed. The corner ponts of each mage were etracted and matched b the procedure eplaned above. The net step s to relate 1963 and 1971 campus mages and 1939 and 1950 Crawfordsvlle mages. Fgures 1 and show for each mage par the matchng ponts dentfed n both mages. These matched pars were then pped nto a Java program bult wth ArcObjects and the unreferenced mages were thereb rectfed and referenced. The left mage of Fgure 3 shows the automatcall referenced 1963.tff under 1971.tff. The rght mage of Fgure 3 shows a detaled vew the rght half of whch s output from automated georeferencng dark area the 1963 mage contrasted wth the 1971 reference mage on the left half. The roads are connected qute well at the border of both mages. From the Crawfordsvlle tests Fgure 4 the left mage shows the manuall referenced 1939 data and the rght mage shows the automatcall georeferenced 1950 mage lad over the 1939 mage. Fgure 5 shows the detaled vew of the comparson between the manuall referenced 1939 mage and the 1950 automated result. The rver and forest features are well connected at the border n both mages. 4. Concluson and future research Smlar aeral photos can be georeferenced b the proposed automated methodolog and the results are useful for applcatons that do not requre hgh accurac or as an ntal appromaton to a more rgorous procedure. There are several lmtatons that must be overcome before the process can be full automated and operatonalzed. The Journal of Terrestral Observaton Volume Number 1 nter 010

7 6 Jae Sung Km Chrstopher C. Mller and James Bethel Fgure 1. Matched ponts from 1963 and 1971 aeral photo on Purdue Campus. Fgure. Matched ponts from 1939 and 1950 aeral photos of Crawfordsvlle ndana. Fgure 3. Left: Automatcall referenced mage 1963 overlad b reference mage 1971 Rght: Detaled vew of referencng left lght: 1971 rght dark: The Journal of Terrestral Observaton Volume Number 1 nter 010

8 Automated georeferencng of aeral photograph 63 Fgure 4. Manuall referenced 1939 aeral photo left and 1950 automatcall georeferenced photo rght 30% transparent overlad on the 1939 photo. Fgure 5. Automated result from 1950 Crawfordsvlle ndana left lght and manuall referenced 1939 photo rght dark. The Journal of Terrestral Observaton Volume Number 1 nter 010

9 64 Jae Sung Km Chrstopher C. Mller and James Bethel 1. The etent and resoluton of the photos must be smlar.. There must be an adequate number of common persstentl dentfable features n both mages. 3. The software must have access to an ArcGS lcense propretar epensve. 4. mager must be near vertcal. 5. Terran relef must be a small fracton of the flng heght. Because ths procedure reles on dentfng mage objects that are not onl unque but persst across dfferent ears mager sets t s mportant that the source mages contan man-made nfrastructure. The angles lnes and shapes of the bult envronment tpcall match well from ear to ear but thus far t has proved mportant to fnd them n largel the same place on each mage e.g. n the upper left corner n 1963 and n e found that the correlaton between wndow sze and the number of corner ponts plas a ver mportant role n the outcome of ths procedure. mages wth sgnfcantl dssmlar spatal footprnts tend to cause false matchng or falure of matchng and negatvel affect the ablt to dentf shared locatons. As ths research progresses attenton wll be pad to reducng the amount of smlart requred between pars of mages. Addtonall nterest pont detectors other than the Harrs corner detector wll be tested n an effort to ether choose a sngle best corner detector or to develop detector profles that par certan data crcumstances wth best-ft corner detectors. Herarchcal methods also seem to be well suted to ths problem. e wll lkewse test non-propretar transformaton utltes n order to sever the dependence on costl propretar software. References Derpans K The Harrs Corner Detector. Techncal report Department of Computer Scence and Engneerng York Unverst Toronto Ontaro Canada. Envronmental Sstems Research nsttute nc. ESR Buldng ArcGS Engne applcatons usng Java-Concepts and Samples [onlne]. ESR. Avalable from: [accessed 4 Februar 009]. Fschler M. and Bolles M.R Random sample consensus: A paradgm for model fttng wth applcaton to mage analss and automated cartograph. Communcatons of the Assocaton for Computng Machner 4: Gonzalez R.C. oods R.E. and Eddns S.L Dgtal mage Processng usng Matlab. Upper Saddle Rver NJ: Prentce Hall. The Journal of Terrestral Observaton Volume Number 1 nter 010

10 Automated georeferencng of aeral photograph 65 Harrs C. and Stephens M A combned Corner and Edge Detector. n Proceedngs of the 4th Alve Vson Conference ndana Geographc nformaton Councl ndanamap. GC. Avalable from: [accessed 14 Februar009] Mkhal E.M. Bethel J.S. and McGlone J.C ntroducton to Modern Photogrammetr. New York: John le & Sons. Moravec H Obstacle avodance and navgaton n the real world b a seeng robot rover. Techncal report CMU-R-TR Robotcs nsttute Carnege Mellon Unverst doctoral dssertaton Stanford Unverst. Stottnger J Local Colour Features for mage Retreval. A More Dstnct Coloured Scale-nvarant nterest Pont Detector. Saarbrucken German: VDM. The Journal of Terrestral Observaton Volume Number 1 nter 010