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Journal : Proceeding of the Electrical Engineering Computer Science and Informatics

Precise Wide Baseline Stereo Image Matching for Compact Digital Cameras Martinus Edwin Tjahjadi; Fourry Handoko
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 4: EECSI 2017
Publisher : IAES Indonesia Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (944.291 KB) | DOI: 10.11591/eecsi.v4.1015

Abstract

Numerous  image  matching  methods  for  wide range  of  applications  have  been  invented  in  the  last  decade. When high precision  and reliability  of the  object space  point coordinates  is  highly  demanding,  a  stereo  image  matching method which can produce conjugate point of images and a standard deviation of  the  matched point  is  examined. In  this approach, image gradients are used locally to seek a conjugate patch.  The  normalized  cross  correlation  is  first  utilized  to estimate an approximate location of the conjugate patch between two normalized images. Then the location of conjugate patch is further refined by using Gaussian-Newton least squares image matching. Both radiometric and geometric parameters of least squares models are used selectively in seeking the best possible accuracy.  Iterative  computation is  conducted to  incrementally refine the geometric location of the conjugate point. After a matched patch has been found, a variant-covariant matrix of the parameter is analyzed to inform the precision of the conjugate points  both  on  images  and  object  space.  This  method  can compute high precision object space points and some examples demonstrate the insight of the approach.
Single Frame Resection of Compact Digital Cameras for UAV Imagery Martinus Edwin Tjahjadi; Fourry Handoko
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 4: EECSI 2017
Publisher : IAES Indonesia Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1053.583 KB) | DOI: 10.11591/eecsi.v4.1070

Abstract

Recently, UAVs (Unmanned Aerial Vehicles) gaina wider acceptance from many disciplines. One major applicationis for monitoring and mapping. Flying beyond eye sightautonomously and collecting data over large areas are theirobvious advantages. To support a large scale urban city mapping,we have developed a UAV system which can carry a compactdigital camera as well as a navigational grade of a GlobalPositioning System (GPS) board mounted on the vehicle.Unfortunately, such a navigational system fails to providesufficient accuracy required to process images become a largescale map. Ubiquitous digital compact cameras, despite their lowcost benefits, are widely known to suffer instabilities in theirinternal lenses and electronics imaging system. Hence thesecameras are less suitable for mapping related purposes. However,this paper presents a photogrammetric technique to preciselydetermine intrinsic and extrinsic camera parameters ofphotographed images provided that sufficient numbers ofsurveyed control points are available. A rigorous Mathematicalmodel is derived to compute each image position with respect tothe imaging coordinate system as well as a location of theprincipal point of an image sensor and the focal length of thecamera. An iterative Gaussian-Newton least squares adjustmentmethod is utilized to compute those parameters. Finally, surveyeddata are processed and elaborated to justify the mathematicalmodels.
A Relative Rotation between Two Overlapping UAV's Images Martinus Edwin Tjahjadi; Fransisca Agust
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 5: EECSI 2018
Publisher : IAES Indonesia Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (646.445 KB) | DOI: 10.11591/eecsi.v5.1681

Abstract

In this paper, we study the influence of varying baseline components on the accuracy of a relative rotation between two overlapping aerial images taken form UAV flight. The case is relevant when mosaicking UAV's aerial images by registering each individual image. Geotagged images facilitated by a navigational grade GPS receiver on board inform the camera position when taking pictures. However, these low accuracies of geographical coordinates encoded in an EXIF format are unreliable to depict baseline vector components between subsequent overlapping images. This research investigates these influences on the stability of rotation elements when the vector components are entered into a standard coplanarity condition equation to determine the relative rotation of the stereo images. Assuming a nadir looking camera on board while the UAV platform is flying at a constant height, the resulted vector directions are utilized to constraint the coplanarity equation. A detailed analysis of each variation is given. Our experiments based on real datasets confirm that the relative rotation between two successive overlapping image is practically unaffected by the accuracy of positioning method. Furthermore, the coplanarity constraint is invariant with respect to a translation along the baseline of the aerial stereo images.