Abstract
In some situations, the total scene of human vision cannot capture in a single shot of camera sensor, and image mosaic is a technique of forming a large image by combining more than one frame of a scene. This paper demonstrates a simple and novel approach for a real-time image mosaicing technique implemented with a standalone rapid prototype Raspberry Pi2 device with a camera sensor. Mosaicing many video frames of having similar scenes are a time-consuming process and lead to inconsistency between frames of the overlap region. Instead of mosaicing all capture video frames, only every nth frame is considered for mosaicing technique, and filtering video frames are processed for every nth frame of a video sequence. Image mosaicing process starts with corner point detection followed by feature point extraction, matching, geometric transformation, hamming distance and finally wind up with warping and blending.
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References
S.W. Chew, P. Lucey, S. Lucey, J. Saraqih, J.F. Cohn, I. Matthews, S. Sridharan, In the pursuit of effective affective computing: the relationship between features and registration. IEEE Trans. Syst. Man Cybern. Part B Cybern. 42, 1006–1016 (2012)
M. Brown, D.G. Lowe, Automatic panoramic image stitching using invariant features. Int. J. Comput. Vis. 74(1), 59–73 (2007)
B.S. Kim, S.H. Lee, N.I. Cho, Real-time panorama image synthesis by fast camera pose estimation, in Proceedings of the Asia-Pacific Signal Information Processing Association Annual Summit and Conference (APSIPA ASC), Dec 2012, pp. 1–4
K.S.V. Prathap, S.A.K. Jilani, P.R. Reddy, A real-time image mosaicing using scale invariant feature transform. Indian J. Sci. Technol. 9(12) (2016). https://doi.org/10.17485/ijst/2016/v9i12/88175
M. Sharma, Image mosaicing and producing a panoramic visibility. Int. J. Recent. Innov. Trends Comput. Commun. 2(2), 198–201 (2014)
T.E. Choe, I. Cohen, M. Lee, G. Medioni, Optimal global mosaic generation from retinal images, in The 18th International Conference on Pattern Recognition, ICPR 2006, vol 03 (IEEE Computer Society, Washington, DC, USA, 2006), pp. 681–684
V. Tom, P. Aymeric, G. Malandain, P. Xavier, A. Nicholas, Robust mosaicing with correction of motion distortions and tissue deformation for in vivo fibered microscopy. Med. Image Anal. 10(5), 673–692 (2006)
N.R. Gracias, J. Santos-Victor, Underwater video mosaics as visual navigation maps. Comput. Vis. Image Underst. 79(1), 66–91 (2001)
P. Sand, S. Teller, Video matching. ACM Trans. Graph. 23(3), 529–599 (2004)
http://www.raspberrypi.org/help/faqs/. Accessed 15 June 2014
S. Peleg, J. Herman, Panoramic mosaics by manifold projection, in Proceedings of the Conference on Computer Vision and Pattern Recognition, pp. 338–343 (1997)
M. Nixon, A. Aguado, Feature Extraction and Image Processing, 2nd edn. (Oxford-Butterworth, Heinemann, Newnes, 2008)
E. Rosten, R. Porter, T. Drummond, Faster and better: a machine learning approach to corner detection. IEEE Trans. Pattern Anal. Mach. Intell. 32(1), 105–119 (2010)
T. Kekec, A. Yildirim, M. Unel, A new approach to real-time mosaicing of aerial images. Rob. Auton. Syst. 62, 1755–1767 (2014)
R. Ortiz, FREAK: fast retina key point, in CVPR 12 Proceedings of the 2012 IEEE Conference on Computer Vision and Pattern Recognition, pp. 510–517, June 2012
Y. Yan, H. Xia, S. Huang, W. Xiao, An improved matching algorithm for feature points matching, in ICSPCC-2014, pp. 292–296 (2014)
K.S.V. Prathap, S.A.K. Jilani, P.R. Reddy, A critical review on image mosaicing, in International Conference on Computer Communications (ICCCI16), Jan 2016. https://doi.org/10.1109/iccci.2016.7480028
L. Yu, Z. Yu, Y. Gong, An improved ORB algorithm of extracting and matching features. Int. J. Signal Process. Image Process. Pattern Recogn. 8(5), 117–126 (2015)
M. El-Saban, M. Izz, A. Kaheel, Fast stitching of videos captured from freely moving devices by exploiting temporal redundancy, in Proceedings of the IEEE International Conference on Image Processing (Hong Kong, 2010), pp. 1193–1196
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Prathap, K.S.V., Jilani, S.A.K., Reddy, P.R. (2018). A Real-time Image Mosaicing Using Onboard Computer. In: Dash, S., Naidu, P., Bayindir, R., Das, S. (eds) Artificial Intelligence and Evolutionary Computations in Engineering Systems. Advances in Intelligent Systems and Computing, vol 668. Springer, Singapore. https://doi.org/10.1007/978-981-10-7868-2_35
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DOI: https://doi.org/10.1007/978-981-10-7868-2_35
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