Robust Affine Invariant Descriptors

An approach is developed for the extraction of affine invariant descriptors by cutting object into slices. Gray values associated with every pixel in each slice are summed up to construct affine invariant descriptors. As a result, these descriptors are very robust to additive noise. In order to establish slices of correspondence between an object and its affine transformed version, general contour (GC) of the object is constructed by performing projection along lines with different polar angles. Consequently, affine in-variant division curves are derived. A slice is formed by points fall in the region enclosed by two adjacent division curves. To test and evaluate the proposed method, several experiments have been conducted. Experimental results show that the proposed method is very robust to noise.

[1]  Chun-Hsiung Fang,et al.  Synthesized affine invariant function for 2D shape recognition , 2007, Pattern Recognit..

[2]  Ming Li.  Modeling autocorrelation functions of long-range dependent teletraffic series based on optimal approximation in Hilbert space—A further study , 2007 .

[3]  Yuan Yan Tang,et al.  Information Distribution of the Central Projection Method for Chinese Character Recognition , 2000, J. Inf. Sci. Eng..

[4]  Tardi Tjahjadi,et al.  Clique descriptor of affine invariant regions for robust wide baseline image matching , 2010, Pattern Recognit..

[5]  Jezekiel Ben-Arie,et al.  Pictorial Recognition of Objects Employing Affine Invariance in the Frequency Domain , 1998, IEEE Trans. Pattern Anal. Mach. Intell..

[6]  Wageeh Boles,et al.  Wavelet-based affine invariant representation: a tool for recognizing planar objects in 3D space , 1997, IEEE Trans. Pattern Anal. Mach. Intell..

[7]  Thomas H. Reiss,et al.  The revised Fundamental Theorem of Moment Invariants , 1991, IEEE Trans. Pattern Anal. Mach. Intell..

[8]  Alexander Kadyrov,et al.  Affine invariant features from the trace transform , 2004, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[9]  Ming Li.  Generation of teletraffic of generalized Cauchy type , 2010 .

[10]  Roland T. Chin,et al.  On Image Analysis by the Methods of Moments , 1988, IEEE Trans. Pattern Anal. Mach. Intell..

[11]  Wesley E. Snyder,et al.  Application of Affine-Invariant Fourier Descriptors to Recognition of 3-D Objects , 1990, IEEE Trans. Pattern Anal. Mach. Intell..

[12]  Mahmoud I. Khalil,et al.  A Dyadic Wavelet Affine Invariant Function for 2D Shape Recognition , 2001, IEEE Trans. Pattern Anal. Mach. Intell..

[13]  Esa Rahtu,et al.  Affine invariant pattern recognition using multiscale autoconvolution , 2005, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[14]  Zhongjie Wang,et al.  Improved Generalized Belief Propagation for Vision Processing , 2011 .

[15]  Ming-Kuei Hu,et al.  Visual pattern recognition by moment invariants , 1962, IRE Trans. Inf. Theory.

[16]  Ming Li,et al.  Representation of a Stochastic Traffic Bound , 2010, IEEE Transactions on Parallel and Distributed Systems.

[17]  Ming Li.  Fractal Time Series—A Tutorial Review , 2010 .

[18]  Yuan Yan Tang,et al.  New method for feature extraction based on fractal behavior , 2002, Pattern Recognit..

[19]  Kidiyo Kpalma,et al.  Affine invariance contour descriptor based on iso-area normalisation , 2007 .

[20]  Ming Li,et al.  Modeling network traffic using generalized Cauchy process , 2008 .

[21]  Nikolaos Mitianoudis,et al.  Robust Recognition of Planar Shapes Under Affine Transforms Using Principal Component Analysis , 2007, IEEE Signal Processing Letters.

[22]  Jan Flusser,et al.  Pattern recognition by affine moment invariants , 1993, Pattern Recognit..

[23]  Ming Li,et al.  mBm-Based Scalings of Traffic Propagated in Internet , 2011 .

[24]  Guojun Lu,et al.  Review of shape representation and description techniques , 2004, Pattern Recognit..

[25]  Hamid Soltanian-Zadeh,et al.  Rotation-invariant multiresolution texture analysis using Radon and wavelet transforms , 2005, IEEE Transactions on Image Processing.

[26]  Abdulkerim Çapar,et al.  Gradient-based shape descriptors , 2008, Machine Vision and Applications.

[27]  Jianwei Zhang,et al.  Vision Processing for Realtime 3-D Data Acquisition Based on Coded Structured Light , 2008, IEEE Transactions on Image Processing.

[28]  Carlo Cattani,et al.  Harmonic wavelet approximation of random, fractal and high frequency signals , 2010, Telecommun. Syst..

[29]  Mohamed S. Kamel,et al.  Wavelet approximation-based affine invariant shape representation functions , 2006, IEEE Transactions on Pattern Analysis and Machine Intelligence.