Affine invariants for object recognition using the wavelet transform

An Affine Invariant Function using PCA Bases with an Application to Within-Class Object Recognition

“…Fourier analysis and wavelet decomposition are two well-studied examples [3], [4], [5]. In these cases, the bases, used for boundary analysis, are mathematically well-defined to serve some specific analysis tasks.…”

“…These signals are then used to construct affine invariant functions. The choice of the signals, the decomposition levels and the wavelet functions used, have all resulted in a number of different approaches [1], [2], [3], [4], [5].…”

Euler Vector for Search and Retrieval of Gray-Tone Images

“…1) Spatial features are characterized by the gray-levels or colors and their distributions like amplitude and histograms [28], [39]. 2) Transform features provide the frequency domain information of the image, obtained by zonal filtering in the selected transform space e.g., Fourier descriptor, DCT, with applications to shape analysis [20], [29], [44]. 3) Edges and boundaries characterizing object boundaries and shape may be extracted using gradient operators.…”

Robust Recognition of Planar Shapes Under Affine Transforms Using Principal Component Analysis

“…The object boundary is analyzed at different scales, yielding to the approximation and the detail signals, which are then used for the construction of affine invariant functions. The choice of the signals, the number of decomposition levels and the wavelet functions used, have all resulted in a number of different approaches [4], [5], [6], [7], [8]. Unfortunately, the performance of the above methods is strongly affected by the non-uniform sampling introduced by the boundary extraction process and the parameter transformation problem described above.…”