Abstract
We present a novel image transform called Scale Manipulation Features (SMF). The transform calculates affine invariant features of objects in a global manner and avoids using any sort of edge detection. The transform can be used for registration of affine transformed images in the presence of non homogenous illumination changes and for estimation of the illumination changes. The computational load of the method is relatively low since it is linear in the data size. In this paper we introduce the transform and demonstrate its applications for illumination compensation and for object registration in the presence of an affine geometric transformation and varying illumination.
Chapter PDF
Similar content being viewed by others
Keywords
References
Shashua, A.: Geometry and Photometry in 30 Visual Recognition. PhD thesis, MIT Dept of Brain and Cognitive Science (August 1992)
Hallinan, P.W.: A low-dimensional representation of human faces for arbitrary lighting conditions. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 995–999 (1994)
Belhumeur, P., Kriegman, D.: What Is the Set of Images of an Object under All Possible Lighting Conditions. Intl J. Computer Vision 28, 245–260 (1998)
Basri, R., Jacobs, D.W.: Lambertian Reflectance and Linear Subspaces. IEEE Transactions on Pattern Analysis and Machine Intelligence 25(2), 218–233 (2003)
Tuytelaars, T., Van Gool, L.: Matching Widely Separated Views Based on Affine Invariant Regions. Intl J. Computer Vision 1(59), 61–85 (2004)
Lowe, D.G.: Distinctive image features from scale-invariant keypoints. International Journal of Computer Vision 60(2), 91–110 (2004)
Matas, J., Chum, O., Urban, M., Pajdla, T.: Robust wide baseline stereo from maximally stable extremal regions. In: Proc. of British Machine Vision Conference, pp. 384–396 (2002)
Rahtu, E., Salo, M., Heikkila, J.: Affine invariant pattern recognition using multiscale autoconvolution. IEEE Transactions on Pattern Analysis and Machine Intelligence 27(6), 908–918 (2005)
Flusser, J., Suk, T.: Pattern recognition by affine moment invariants. Pattern Recognition 26(1), 167–174 (1993)
Yang, Z., Cohen, F.S.: Cross-weighted moments and affine invariants for image registration and matching. IEEE Trans. Pattern Analysis and Machine Intelligence 21(8), 804–814 (1999)
Petrou, M., Kadyrov, A.: Affine invariant features from the trace transform. IEEE Trans. Pattern Analysis and Machine Intelligence 26(1), 30–44 (2004)
Mindru, F., Tuytelaars, T., van Gool, L., Moons, T.: Moment Invariants for Recognition under Changing Viewpoint and Illumination. Computer Vision and Image Understanding 94, 3–27 (2004)
Francos, J.M., Hagege, R., Friedlander, B.: Estimation of Multi-Dimensional Homeomorphisms for Object Recognition in Noisy Environments. In: Thirty Seventh Asilomar Conference on Signals, Systems, and Computers (2003)
Frenkel, R., Francos, J.: Registration of geometric deformations in the presence of varying illumination. In: Proc. IEEE International Conference on Image Processing 2007, vol. 3, pp. 489–492 (2007)
Bentolila, K., Francos, J.: Affine and Illumination Estimation Using Scale Manipulation Transform (to appear)
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
Bentolila, K., Francos, J.M. (2009). Joint Affine and Illumination Estimation Using Scale Manipulation Features. In: Foggia, P., Sansone, C., Vento, M. (eds) Image Analysis and Processing – ICIAP 2009. ICIAP 2009. Lecture Notes in Computer Science, vol 5716. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04146-4_90
Download citation
DOI: https://doi.org/10.1007/978-3-642-04146-4_90
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-04145-7
Online ISBN: 978-3-642-04146-4
eBook Packages: Computer ScienceComputer Science (R0)