Volume 34 #1

Contents

1. The rates of evolution of songs and speciation in grasshoppers from subfamily Gomphocerinae (Orthoptera, Acrididae, Gomphocerinae)
2. Disruptive song – an effective mechanism to prevent copulation in stink-bugs Pentatoma rufipes
3. The role of acoustic and vibration signals in host-parasitoid unteraction in Tachinidae (Diptera) and stink-bugs (Pentatomidae)
4. Fine structure of receptive fields of orientation-selective ganglion cells in goldfish retina
5. On optimal visualization of images on photoemission displays with significant dispersion of efficiency of individual elements
6. Vanishing point detection for monocular camera extrinsic calibration under translation movement
7. A linear regression method robust to extreme stationary clutter
8. Filtering erroneous frame-by-frame results for planar rectangular objects localization in a video using matching transform graph
9. Fast filtering and back projection for CT image reconstruction
10. 1-point RANSAC for axial rotation angle estimation by tomographic projections

This paper presents a RANSAC-based algorithm for determining the axial rotation angle of an object from a pair of its tomographic projections. An equation is obtained for calculating the rotation angle using one correct keypoints match of two tomographic projections. The proposed algorithm includes following steps: keypoints detection and matching, rotation angle estimation for all matches, inliers selection with the RANSAC algorithm, finally, refining resulting angle by minimizing the Sampson’s distance for the remaining matches. To validate the proposed method an experimental comparison against methods based on analysis of the distribution of the angles computed from all matches is conducted.

Key words: circular motion estimation, camera circular motion, visual odometry, relative motion estimation, RANSAC, computed tomography, digital X-ray imaging

DOI: 10.31857/S0235009220010060

References:

• Buzmakov A.V., Asadchikov V.E., Zolotov D.A., Roshchin B.S., Dymshits YU.M., Shishkov V.A., Chukalina M.V., Ingacheva A.S., Ichalova D.E., Krivonosov Yu.S., D’yachkova I.G., Baltser M., Kassele M., Chilingaryan S., Kopmann A. Laboratornye mikrotomografy: konstruktsiya i algoritmy obrabotki dannykh [Laboratory Microtomographs: Design and Data Processing Algorithms]. Kristallografiya [Сrystallography]. 2018. V. 63 (6). P. 1007–1011 (in Russian).
• Buzmakov A.V., Asadchikov V.E., Zolotov D.A., Chukalina M.V., Ingacheva A.S., Krivonosov Yu.S. Laboratornye rentgenovskie mikrotomografy: metody predobrabotki eksperimental’nyh dannyh [Laboratory X-ray Microtomography: Ways of Processing Experimental Data]. Izvestiya RAN. Seriya Fizicheskaya [Bulletin of the Russian Academy of Sciences: Physics]. 2019. V. 83 (2). P. 194–197 (in Russian).
• Ovchinkin A.A., Ershov E.I. Algoritm opredeleniya polozheniya puchka epipolyarnyh linij dlya sluchaya pryamolinejnogo dvizheniya kamery [Algorithm for determination the position of epipolar lines beam in case of straightforward motion]. Sensornye sistemy [Sensory Systems]. 2018. V. 32 (1). P. 42–49 (in Russian).
• Bay H., Tuytelaars T., Van Gool L. Surf: Speeded up robust features. European conference on computer vision. Springer. 2006. P. 404–417. DOI:10.1007/11744023_32
• Bircher B.A., Meli F., Küng A., Thalmann R. A geometry measurement system for a dimensional cone-beam CT. 8th Conference on Industrial Computed Tomography. Wels, Austria. 2018.
• Buratti A., Bredemann J., Pavan M., Schmitt R., Carmignato S. Industrial X-Ray Computed Tomography. Springer. 2018. P. 333–369. DOI: 10.1007/978-3-319-59573-3_9
• Chung K., Schad L. R., Zöllner F.G. Tomosynthesis implementation with adaptive online calibration on clinical c-arm systems. International journal of computer assisted radiology and surgery. 2018. V. 13 (10). P. 1481–1495. DOI: 10.1007/s11548-018-1810-y
• Civera J., Grasa O.G., Davison A.J., Montiel J. 1-point ransac for ekf-based structure from motion. 2009 IEEE/RSJ International Conferenceon Intelligent Robots and Systems. IEEE. 2009. P. 3498–3504. DOI: 10.1109/iros.2009.5354410
• Civera J., Grasa O.G., Davison A.J., Montiel J. 1-point ransacfor extended kalman filtering: Application to real-time structure from motionand visual odometry. Journal of Field Robotics. 2010. V. 27 (5). P. 609–631. DOI: 10.1002/rob.20345
• Defrise M., Vanhove C., Nuyts J. Perturbative refinement of the geometric calibration in pinhole spect. IEEE transactions on medical imaging. 2008. V. 27 (2). P. 204–214. DOI: 10.1109/tmi.2007.904687
• Dewulf W., Kiekens K., Tan Y., Welkenhuyzen F., Kruth J.- P. Uncertainty determination and quantification for dimensional measurementswith industrial computed tomography. CIRP Annals. 2013. V. 62 (1). P. 535–538. DOI: 10.1016/j.cirp.2013.03.017
• Feldkamp L.A., Davis L., Kress J.W. Practical cone-beam algorithm. Josa a1. 1984. V. 1 (6). P. 612–619. DOI: 10.1016/j.cirp.2013.03.017
• Ferrucci M., Ametova E., Carmignato S., Dewulf W. Evaluating theeffects of detector angular misalignments on simulated computed tomographydata. Precision Engineering. 2016. V. 45. P. 230–241. DOI: 10.1016/j.precisioneng.2016.03.001
• Ferrucci M., Leach R.K., Giusca C., Carmignato S., Dewulf W. Towards geometrical calibration of x-ray computed tomography systems – a review. Measurement Science and Technology. 2015. V. 26 (9). P. 092003. DOI: 10.1088/0957-0233/26/9/092003
• Golub G.H. Least squares, singular values and matrix approximations. Aplikace matematiky. 1968. V. 13 (1). P. 44–51. DOI: 10.1007/978-3-662-39778-7_10
• Grewal M.S. Kalman filtering. Springer. 2011. DOI: 10.1007/978-3-642-04898-2_321
• Hermanek P., Ferrucci M., Dewulf W., Carmignato S. Optimized reference object for assessment of computed tomography instrument geometry. 7th Conference on Industrial Computed Tomography. 2017. P. 7–8
• Hernández C., Schmitt F., Cipolla R. Silhouette coherence forcamera calibration under circular motion. IEEE transactions on patternanalysis and machine intelligence. 2007. V. 29 (2). P. 343–349. DOI: 10.1109/tpami.2007.42
• Hu M., McMenemy K., Ferguson S., Dodds G., Yuan B. Epipolar geometry estimation based on evolutionary agents. Pattern Recognition. 2008. V. 41 (2). P. 575–591. DOI: 10.1016/j.patcog.2007.06.016
• Katsevich A. An improved exact filtered backprojection algorithm forspiral computed tomography. Advances in Applied Mathematics. 2004. V. 32 (4). P. 681–697. DOI: 10.1016/s0196-8858(03)00099-x
• Kesminiene A., Cardis E. Cancer risk from paediatric computedtomography scanning: Implications for radiation protection in medicine. Annals of the ICRP. 2018. V. 47 (3–4). P. 113–114. DOI: 10.1177/0146645318756236
• Kumar J., Attridge A., Wood P., Williams M.A. Analysis of the effect of cone-beam geometry and test object configuration on the measurement accuracy of a computed tomography scanner used for dimensional measurement. Measurement Science and Technology. 2011. V. 22 (3). P. 035105. DOI: 10.1088/0957-0233/22/3/035105
• Kunina I., Panfilova E., Gladkov A. Matching of sar and optical images by independent referencing to vector map. J. Zhou. 2019. V. 11041. DOI: 10.1117/12.2523132
• Mairhofer S., Pridmore T., Johnson J., Wells D.M., Bennett M.J., Mooney S.J., Sturrock C.J. X-ray computed tomography of crop plantroot systems grown in soil. Current Protocols in Plant Biology. 2017. V. 2 (4). P. 270–286. DOI: 10.1002/cppb.20049
• Mendonça P.R., Wong K.-Y.K., Cipolla R. Camera pose estimationand reconstruction from image profiles under circular motion. European Conference on Computer Vision. Springer. 2000. P. 864–877. DOI: 10.1007/3-540-45053-x_55
• Muders J., Hesser J. Stable and robust geometric self-calibrationfor cone-beam ct using mutual information. IEEE Transactions on NuclearScience. 2014. V. 61 (1). P. 202–217. DOI: 10.1109/tns.2013.2293969
• Nistér D. An efficient solution to the five-point relative pose problem. IEEE transactions on pattern analysis and machine intelligence. 2004. V. 26 (6). P. 0756–777. DOI: 10.1109/tpami.2004.17
• Scaramuzza D. 1-point-ransac structure from motion for vehicle-mounted cameras by exploiting non-holonomic constraints. International journal of computer vision. 2011a. V. 95 (1). P. 74–85. DOI: 10.1007/s11263-011-0441-3
• Scaramuzza D. Performance evaluation of 1-point-ransac visualodometry. Journal of Field Robotics. 2011b. V. 28 (5). P. 792–811. DOI: 10.1002/rob.20411
• Scaramuzza D., Fraundorfer F., Siegwart R. Real-time monocularvisual odometry for on-road vehicles with 1-point ransac. 2009 IEEEInternational Conference on Robotics and Automation. IEEE. 2009. P. 4293–4299. DOI: 10.1109/robot.2009.5152255
• Tropin D.V., Nikolaev D.P., Slugin D.G. The method of image alignment based on sharpness maximization. J. Zhou. 2019. V. 11041. DOI: 10.1117/12.2522903
• Van Cuong N., Heo M.B., Jee G.-I. 1-point ransac based robustvisual odometry. J. Korean GNSS Society. 2013. V. 2 (1). P. 81–89. DOI: 10.11003/jkgs.2013.2.1.081
• Vianello A., Ackermann J., Diebold M., Jähne B. Robust houghtransform based 3d reconstruction from circular light fields. Proceedings ofthe IEEE Conference on Computer Vision and Pattern Recognition. 2018. P. 7327–7335.19 DOI: 10.1109/cvpr.2018.00765
• Weiß D., Lonardoni R., Deffner A., Kuhn C. Geometric imagedistortion in flat-panel x-ray detectors and its influence on the accuracy ofct-based dimensional measurements. iCT conference. 2012. DOI: 10.1016/b978-0-12-388429-9.00008-x
• Welkenhuyzen F., Boeckmans B., Tan Y., Kiekens K., Dewulf W., Kruth J.-P. Investigation of the kinematic system of a 450 kv ct scanner andits influence on dimensional ct metrology applications. Proceedings of the 5th International Conference on Industrial Computed Tomography. 2014. P. 217–225.
• Wenig P., Kasperl S. Examination of the measurement uncertainty ondimensional measurements by x-ray computed tomography. Proceedingsof 9th European Conference on Non-Destructive Testing (ECNDT), Berlin,Germany. 2006.s
• Wong K.-Y., Cipolla R. Structure and motion from silhouettes. Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001. 2001. V. 2. IEEE. P. 217–222. DOI: 10.1109/iccv.2001.937627
• Xu Y., Yang S., Ma J., Li B., Wu S., Qi H., Zhou L. Simultaneous calibration phantom commission and geometry calibration in cone beam ct. Physics in Medicine, Biology. 2017. V. 62 (17). № 375. DOI: 10.1088/1361-6560/aa77e5
• Yang K., Li X., George Xu X., Liu B. Direct and fast measurementof ct beam filter profiles with simultaneous geometrical calibration. Medical physics. 2017. V. 44 (1). P. 57–70. DOI: doi.org/10.1002/mp.12024
• Zhang F., Du J., Jiang H., Li L., Guan M., Yan B. Iterative geometric calibration in circular cone-beam computed tomography. Optik-International Journal for Light and Electron Optics. 2014. V. 125 (11). P. 2509–2514. DOI: 10.1016/j.ijleo.2013.10.090