Abstract
Biologically inspired schemes are a source for the improvement of visual systems. Real-time implementation of image processing algorithms is constrained by the large amount of data to be processed. Full image processing is many times unnecessary since there are many pixels that suffer a small change or not suffer any change at all. A strategy based on delivering and processing pixels, instead of processing the complete frame, is presented. The pixels that have suffered higher changes in each frame, ordered by the absolute value of its change, are read-out and processed. Two examples are shown: a morphological motion detection algorithm and the Horn and Schunck optical flow algorithm. Results show that the implementation of this strategy achieves execution time speed-up while keeping results comparable to original approaches.
Chapter PDF
Similar content being viewed by others
References
Özalevli, E., Higgins, C.M.: Reconfigurable Biologically Inspired Visual Motion Systems Using Modular Neuromorphic VLSI Chips. IEEE Transactions on Circuits and Systems 52(1), 79–92 (2005)
Lichtsteiner, P., Posch, C., Delbruck, T.: A 128x128 dB 15 μs Latency Asynchronous Temporal Contrast Vision Sensor. IEEE Journal of Solid-State Circuits 43(2), 566–576 (2008)
Boluda, J.A., Pardo, F.: Speeding-up differential motion detection algorithms using a change-driven data-flow processing strategy. In: Kropatsch, W.G., Kampel, M., Hanbury, A. (eds.) CAIP 2007. LNCS, vol. 4673, pp. 77–84. Springer, Heidelberg (2007)
Pardo, F., Boluda, J.A., Vegara, F., Zuccarello, P.: On the advantages of asynchronous pixel reading and processing for high-speed motion estimation. In: Bebis, G., Boyle, R., Parvin, B., Koracin, D., Remagnino, P., Porikli, F., Peters, J., Klosowski, J., Arns, L., Chun, Y.K., Rhyne, T.-M., Monroe, L. (eds.) ISVC 2008, Part I. LNCS, vol. 5358, pp. 205–215. Springer, Heidelberg (2008)
Silc, J., Robic, B., Ungerer, T.: Processor architecture: from dataflow to superscalar and beyond. Springer, Heidelberg (1999)
Manzanera, A., Richefeu, J.C.: A new motion detection algorithm based on Σ-Δ background estimation. Pattern Recognition Letters 28, 320–328 (2007)
Teng, C.H., Lai, S.H., Chen, Y.S., Hsu, W.H.: Accurate optical flow computation under non-uniform brightness variations. Computer Vision and Image Understanding 97(3), 315–346 (2005)
Díaz, J., Ros, E., Pelayo, F., Ortigosa, E.M., Mota, S.: FPGA-based real-time optical-flow system. IEEE Transactions on Circuits and Systems for Video Technology 16(2), 274–279 (2006)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2009 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Boluda, J.A., Vegara, F., Pardo, F., Zuccarello, P. (2009). Selective Change-Driven Image Processing: A Speeding-Up Strategy. In: Bayro-Corrochano, E., Eklundh, JO. (eds) Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications. CIARP 2009. Lecture Notes in Computer Science, vol 5856. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-10268-4_4
Download citation
DOI: https://doi.org/10.1007/978-3-642-10268-4_4
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-10267-7
Online ISBN: 978-3-642-10268-4
eBook Packages: Computer ScienceComputer Science (R0)