Abstract
Hexagonal image structure is a relatively new and powerful approach to intelligent vision system. The geometrical arrangement of pixels in this structure can be described as a collection of hexagonal pixels. However, all the existing hardware for capturing image and for displaying image are produced based on rectangular architecture. Therefore, it becomes important to find a proper software approach to mimic hexagonal structure so that images represented on the traditional square structure can be smoothly converted from or to the images on hexagonal structure. For accurate image processing, it is critical to best maintain the image resolution after image conversion. In this paper, we present various algorithms for image conversion between the two image structures. The performance of these algorithms will be compared though experimental results.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Horn, B.K.P.: Robot Vision. MIT Press, Cambridge, MA & McGraw-Hill, New York (1986)
Staunton, R.: The Design of Hexagonal Sampling Structures for Image Digitization and Their Use with Local Operators. Image and Vision Computing 7(3), 162–166 (1989)
Wuthrich, C.A., Stucki, P.: An Algorithmic Comparison between Square- and Hexagonal-based Grids. CVGIP: Graphical Models and Image Processing 53(4), 324–339 (1991)
He, X.: 2-D Object Recognition with Spiral Architecture. PhD Thesis. University of Technology, Sydney (1999)
Wu, Q., He, X., Hintz, T.: Virtual Spiral Architecture. In: Proceedings of the International Conference on Parallel and Distributed Processing Techniques and Applications, vol. 1, pp. 399–405 (2004)
Wang, H., Wang, M., Hintz, T., He, X., Wu, Q.: Fractal Image Compression on a Pseudo Spiral Architecture. Australian Computer Science Communications 27, 201–207 (2005)
He, X., Jia, W.: Hexagonal Structure for Intelligent Vision. In: ICICT 2005. Proceedings of International Conference on Information and Communication Technologies, pp. 52–64 (2005)
He, X., Hintz, T., Wu, Q., Wang, H., Jia, W.: A New Simulation of Spiral Architecture. In: IPCV 2006. International Conference on Image Processing, Computer Vision and Pattern Recognition, pp. 570–575 (2006)
Tian, Y., Liu, B., Li, T.: A Local Image Interpolation Method Based on Gradient Analysis. In: ICNN&B 2005. International Conference on Neural Networks and Brain, vol. 2, pp. 1202–1205 (2005)
Sheridan, P., Hintz, T., Alexander, D.: Pseudo-invariant Image Transformations on a Hexagonal Lattice. Image and Vision Computing 18, 907–917 (2000)
He, X., Wang, H., Hur, N., Jia, W., Wu, Q., Kim, J., Hintz, T.: Uniformly Partitioning Images on Virtual Hexagonal Structure. In: IEEE ICARCV 2006. 9th International Conference on Control, Automation, Robotics and Vision, pp. 891–896. IEEE Computer Society Press, Los Alamitos (2006)
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2007 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
He, X., Li, J., Hintz, T. (2007). Comparison of Image Conversions Between Square Structure and Hexagonal Structure. In: Blanc-Talon, J., Philips, W., Popescu, D., Scheunders, P. (eds) Advanced Concepts for Intelligent Vision Systems. ACIVS 2007. Lecture Notes in Computer Science, vol 4678. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74607-2_24
Download citation
DOI: https://doi.org/10.1007/978-3-540-74607-2_24
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-74606-5
Online ISBN: 978-3-540-74607-2
eBook Packages: Computer ScienceComputer Science (R0)