Invariance properties of Gabor filter-based features-overview and applications

For almost three decades the use of features based on Gabor filters has been promoted for their useful properties in image processing. The most important properties are related to invariance to illumination, rotation, scale, and translation. These properties are based on the fact that they are all parameters of Gabor filters themselves. This is especially useful in feature extraction, where Gabor filters have succeeded in many applications, from texture analysis to iris and face recognition. This study provides an overview of Gabor filters in image processing, a short literature survey of the most significant results, and establishes invariance properties and restrictions to the use of Gabor filters in feature extraction. Results are demonstrated by application examples.

[1]  H. Nyquist,et al.  Certain factors affecting telegraph speed , 1924, Journal of the A.I.E.E..

[2]  Dennis Gabor,et al.  Theory of communication , 1946 .

[3]  Leonard J. Porcello,et al.  Optical data processing and filtering systems , 1960, IRE Trans. Inf. Theory.

[4]  Albert H. Nuttall,et al.  Minimum Gabor bandwidth of M orthogonal signals , 1965, IEEE Trans. Inf. Theory.

[5]  Ronald N. Bracewell,et al.  The Fourier Transform and Its Applications , 1966 .

[6]  D. Slepian,et al.  On bandwidth , 1976, Proceedings of the IEEE.

[7]  D. Casasent,et al.  New optical transforms for pattern recognition , 1977, Proceedings of the IEEE.

[8]  Jont B. Allen,et al.  Short term spectral analysis, synthesis, and modification by discrete Fourier transform , 1977 .

[9]  G. Granlund.  In search of a general picture processing operator , 1978 .

[10]  F. Amoroso,et al.  The bandwidth of digital data signal , 1980, IEEE Communications Magazine.

[11]  M. Bastiaans,et al.  Gabor's expansion of a signal into Gaussian elementary signals , 1980, Proceedings of the IEEE.

[12]  A.V. Oppenheim,et al.  The importance of phase in signals , 1980, Proceedings of the IEEE.

[13]  A. Grossmann,et al.  DECOMPOSITION OF HARDY FUNCTIONS INTO SQUARE INTEGRABLE WAVELETS OF CONSTANT SHAPE , 1984 .

[14]  J. Daugman.  Uncertainty relation for resolution in space, spatial frequency, and orientation optimized by two-dimensional visual cortical filters. , 1985, Journal of the Optical Society of America. A, Optics and image science.

[15]  John G. Daugman,et al.  Complete discrete 2-D Gabor transforms by neural networks for image analysis and compression , 1988, IEEE Trans. Acoust. Speech Signal Process..

[16]  Yehoshua Y. Zeevi,et al.  The Generalized Gabor Scheme of Image Representation in Biological and Machine Vision , 1988, IEEE Trans. Pattern Anal. Mach. Intell..

[17]  Benjamin Friedlander,et al.  Detection of transient signals by the Gabor representation , 1989, IEEE Trans. Acoust. Speech Signal Process..

[18]  Stéphane Mallat,et al.  A Theory for Multiresolution Signal Decomposition: The Wavelet Representation , 1989, IEEE Trans. Pattern Anal. Mach. Intell..

[19]  C. von der Malsburg,et al.  Distortion invariant object recognition by matching hierarchically labeled graphs , 1989, International 1989 Joint Conference on Neural Networks.

[20]  Anil K. Jain,et al.  Unsupervised texture segmentation using Gabor filters , 1990, 1990 IEEE International Conference on Systems, Man, and Cybernetics Conference Proceedings.

[21]  Ingrid Daubechies,et al.  The wavelet transform, time-frequency localization and signal analysis , 1990, IEEE Trans. Inf. Theory.

[22]  Joachim M. Buhmann,et al.  Size and distortion invariant object recognition by hierarchical graph matching , 1990, 1990 IJCNN International Joint Conference on Neural Networks.

[23]  Wilson S. Geisler,et al.  Multichannel Texture Analysis Using Localized Spatial Filters , 1990, IEEE Trans. Pattern Anal. Mach. Intell..

[24]  Majid Ahmadi,et al.  Pattern recognition with moment invariants: A comparative study and new results , 1991, Pattern Recognit..

[25]  Anil K. Jain,et al.  Unsupervised texture segmentation using Gabor filters , 1990, 1990 IEEE International Conference on Systems, Man, and Cybernetics Conference Proceedings.

[26]  Moshe Porat,et al.  Can one evaluate the Gabor expansion using Gabor's iterative algorithm? , 1992, IEEE Trans. Signal Process..

[27]  N. Ranganathan,et al.  Gabor filter-based edge detection , 1992, Pattern Recognit..

[28]  Edward H. Adelson,et al.  Shiftable multiscale transforms , 1992, IEEE Trans. Inf. Theory.

[29]  Joachim M. Buhmann,et al.  Distortion Invariant Object Recognition in the Dynamic Link Architecture , 1993, IEEE Trans. Computers.

[30]  Chin-Tu Chen,et al.  An efficient algorithm to compute the complete set of discrete Gabor coefficients , 1994, IEEE Trans. Image Process..

[31]  M. Bastiaans,et al.  Gabor's signal expansion and the Zak transform. , 1994, Applied optics.

[32]  Rolf P. Würtz,et al.  Multilayer dynamic link networks for establishing image point correspondences and visual object recognition , 1995 .

[33]  Dennis F. Dunn,et al.  Optimal Gabor filters for texture segmentation , 1995, IEEE Trans. Image Process..

[34]  Jie Yao,et al.  The generalized Gabor transform , 1995, IEEE Trans. Image Process..

[35]  Hans G. Feichtinger,et al.  Equivalence of DFT filter banks and Gabor expansions , 1995, Optics + Photonics.

[36]  Dennis M. Healy,et al.  A parametric class of discrete Gabor expansions , 1996, IEEE Trans. Signal Process..

[37]  Tai Sing Lee,et al.  Image Representation Using 2D Gabor Wavelets , 1996, IEEE Trans. Pattern Anal. Mach. Intell..

[38]  Marc Geilen,et al.  On the discrete Gabor transform and the discrete Zak transform , 1996, Signal Process..

[39]  Norbert Krüger,et al.  Face recognition by elastic bunch graph matching , 1997, Proceedings of International Conference on Image Processing.

[40]  Helmut Bölcskei,et al.  Frame-theoretic analysis of oversampled filter banks , 1998, IEEE Trans. Signal Process..

[41]  Hao Ling,et al.  Joint time-frequency analysis for radar signal and image processing , 1999, IEEE Signal Process. Mag..

[42]  Jiri Matas,et al.  XM2VTSDB: The Extended M2VTS Database , 1999 .

[43]  S. Qian,et al.  Joint time-frequency analysis , 1999, IEEE Signal Process. Mag..

[44]  Yoshinobu Sato,et al.  Orientation Space Filtering for Multiple Orientation Line Segmentation , 2000, IEEE Trans. Pattern Anal. Mach. Intell..

[45]  Heikki Kälviäinen,et al.  Invariant Shape Recognition using Global Gabor Features , 2000 .

[46]  Pasi Fränti,et al.  Content-based matching of line-drawing images using the Hough transform , 2000, International Journal on Document Analysis and Recognition.

[47]  Qiao Wang.  The shiftability of some wavelet bases , 2000 .

[48]  Qiao Wang.  Classification of Wavelet Bases by Translation Subgroups and Nonharmonic Wavelet Bases , 2000 .

[49]  Hyun Seung Yang,et al.  Invariant object detection based on evidence accumulation and Gabor features , 2001, Pattern Recognit. Lett..

[50]  Heikki Kälviäinen,et al.  Content-Based Image Matching Using Gabor Filtering , 2001 .

[51]  Klaus J. Kirchberg,et al.  Robust Face Detection Using the Hausdorff Distance , 2001, AVBPA.

[52]  Jouko Lampinen,et al.  Bayesian object matching based on MCMC sampling and Gabor filters , 2001, SPIE Optics East.

[53]  Josef Kittler,et al.  Discriminative Regions for Human Face Detection , 2001 .

[54]  Joni-Kristian Kämäräinen,et al.  Fundamental frequency Gabor filters for object recognition , 2002, Object recognition supported by user interaction for service robots.

[55]  Gerald Sommer,et al.  Gabor wavelet networks for efficient head pose estimation , 2002, Image Vis. Comput..

[56]  Josef Kittler,et al.  Invariant Gabor Features for Face Evidence Extraction , 2002, MVA.

[57]  Joni-Kristian Kämäräinen,et al.  Robustness of Gabor Feature Parameter Selection , 2002, MVA.

[58]  Jiri Matas,et al.  Face Detection by Learned Affine Correspondences , 2002, SSPR/SPR.

[59]  J.-K. Kamarainen,et al.  Noise tolerant object recognition using Gabor filtering , 2002, 2002 14th International Conference on Digital Signal Processing Proceedings. DSP 2002 (Cat. No.02TH8628).

[60]  Josef Kittler,et al.  Hypotheses-Driven Affine Invariant Localization of Faces in Verification Systems , 2003, AVBPA.

[61]  Joni-Kristian Kämäräinen.  Feature extraction using Gabor filters , 2003 .

[62]  I. Daubechies,et al.  Framelets: MRA-based constructions of wavelet frames☆☆☆ , 2003 .

[63]  Josef Kittler,et al.  Affine-invariant face detection and localization using GMM-based feature detector and enhanced appearance model , 2004, Sixth IEEE International Conference on Automatic Face and Gesture Recognition, 2004. Proceedings..

[64]  Joni-Kristian Kämäräinen,et al.  Simple Gabor feature space for invariant object recognition , 2004, Pattern Recognit. Lett..

[65]  J. Sampo,et al.  Measuring shiftability of frames of regular translates , 2004, Proceedings of the 6th Nordic Signal Processing Symposium, 2004. NORSIG 2004..

[66]  John Daugman,et al.  Statistical Richness of Visual Phase Information: Update on Recognizing Persons by Iris Patterns , 2001, International Journal of Computer Vision.

[67]  Sang Joon Kim,et al.  A Mathematical Theory of Communication , 2006 .