We test various features for recognition of leaves of wooden species. We compare Fourier descriptors, Zernike moments, Legendre moments and Chebyshev moments. All the features are computed from the leaf boundary only. Experimental evaluation on real data indicates that Fourier descriptors slightly outperform the other tested features.

Edge detection is an important assignment in image processing, as it is used as a primary tool for pattern recognition, image segmentation and scene analysis. Simply put, an edge detector is a high-pass filter that can be applied for extracting the edge points within an image. Edge detection in the spatial domain is accomplished through convolution with a set of directional derivative masks in ...

The fusion of medical images taken at the same slice/part of the body by differentmodalities is very useful technique in medical diagnosis. Medical image fusion tried withwavelet transform methods proved to be image dependent and preservation of highfrequency contents of the image by wavelets are also not satisfactory. In this work, curvelettransform is applied for fusion wi...

Fast algorithms for a wide class of non–separable n–dimensional (nD) discrete unitary K– transforms (DKT) are introduced. They need less 1D DKTs than in the case of the classical radix–2 FFT–type approach. The method utilizes a decomposition of the nDK–transform into the product of a new nD discrete Radon transform and of a set of parallel/independ 1D K–transforms. If the nD K–transform has a s...

The recognition of a person based on biological features are efficient compared with traditional knowledge based recognition system. In this paper we propose Face Recognition using Wrapping Curvelet Transform (FRWCT). The Wrapping Curvelet Transform (WCT) is applied on face images of database and test images to derive coefficients. The obtained coefficient matrix is rearranged to form WCT featu...

The clarity of medical image, which is directly acquired from the scanning machine, is very less. Image enhancement is one of the best and efficient techniques to increase the quality of image. A combined approach of different techniques such as Wavelet, Curvelet and Multiple Kernel Fuzzy C-Means algorithm was carry out in this paper. Wavelet and Curvelet transforms are used for denoising purpo...

In seismic data processing, the reconstruction and interpolation of missing traces are essential tasks. To overcome limitations irregularly sampled data, this paper proposes a method combining smoothing fast iterative soft threshold algorithm (SFISTA) curvelet transform; uses domain as sparse domain. For comparison, contourlet transform is used for different domains, shrinkage-thresholding (FIS...

The curvelet transform is a recently introduced non-adaptive multi-scale transform that have gained popularity in the image processing field. In this paper, we study the effect of customized tiling of frequency content in the curvelet transform. Specifically, we investigate the effect of the size of the coarsest level and its relationship to denoising performance. Based on the observed behavior...