Invariant pattern recognition using ring-projection and dual-tree complex wavelets

Abstract

A novel descriptor is proposed for invariant pattern recognition by using ring-projection and dual-tree complex wavelets. The ring-projection takes the summation of all pixels that lie on the circle with radius r and centre at the centroid of the pattern. This transforms the pattern from a 2-D image to a 1-D signal, so less memory is needed and it is faster than existing 2-D descriptors in the recognition process. Dual-tree complex wavelet transform is applied to the ring-projection since it has the approximate shift-invariant property, which is very important in pattern recognition. Experimental results show that the proposed descriptor in this paper is a feasible choice for invariant pattern recognition.

Shape and Texture Indexes Application to Cell Nuclei Classification

“…For this reason, it is often helpful to distinguish between two classes of characteristics: the shape using global analysis algorithms 29 (projection histograms, 39,45,55 invariant moments, 13,14 etc.) or outline analysis algorithms (Freeman chain code, 3 MSGPR, 23 Fourier descriptors, 8,45,51,53 etc.) and the texture 41,46,54 using statistical analysis, 9,16,17 wavelets transform 8,47,48 or local binary pattern 33,34 for example.…”

Face recognition based on 2DPCA and DWT

“…, v a a (9) where a is the scale factor,and b is the shi ft factor.and one dimensition wavelet transform and inverse transform can be defmed as follows:…”

“…Experimental results show that the implement of 2DPCA is efficienter than one dimensional counterpart's,but the former need many more coefficients. the recent trend of approaches in face recognition involves wavelet-based methods,which is easy to implement and reduces the computation time and resources required [8] [9][1O].In this paper,a method based on 2DPCA and Discrete Wavelet Transform(DWT) is proposed for face recognition. The effectiveness of the proposed method is verified on the ORL database.…”