We develop a unifying perspective on several decompositions exhibiting directional parabolic scaling. In each decomposition, the individual atoms are highly anisotropic at fine scales, with effective support obeying the parabolic scaling principle length ≈ width. Our comparisons allow to extend Theorems known for one decomposition to others. We start from a Continuous Curvelet Transform f → Γf ...

Today’s revolution is mobile communication revolution, which enables us to connect each other worldwide. Due to the enhancement of multimedia and video surveillance services people are more sophisticated. Because of bandwidth requirements and resolution mismatch the designers still striving to provide robust coding technique. In mobile, web applications scalable video coding plays a vital role ...

Throughout the world the common cause of death in humans is lung cancer. It is necessary to detect cancer as early as possible to increase the survival rate. Lung cancer in CT scan images can be classified easily and efficiently using digital image processing techniques. Curvelet transform can extract the features of lung cancer CT scan images proficiently. All extracted feature by curvelet tra...

Abstract— This paper presents a new offline handwritten Devanagari word recognition system. Though Devanagari is the script for Hindi, which is the official language of India, its character and word recognition pose great challenges due to large variety of symbols and their proximity in appearance. In order to extract features which can distinguish similar appearing words, we employ Curvelet Tr...

This paper presents feature level fusion approach using multi resolution Curvelet transform for face and palm biometrics.In this paper feature extraction has been done by taking the curvelet transform of bit quantized images.The curvelet coefficient thus obtained acts as feature set for classification.The five sets of coefficients from five different versions of images are used to train five SV...

In this work, a multi-scale feature point detection algorithm in CT slices based on discrete curvelet transform is presented. Discrete curvelet transformation is applied to input CT slices and the behavior of curvelet coefficients in all the scales are examined. The information in the fine and detail levels which contains the edge and singularity details are processed to extract the feature poi...

A special member of the emerging family of multiscale geometric transforms is the curvelet transform which was developed in the last few years in an attempt to overcome inherent limitations of traditional multistage representations such as wavelets. Mathematical is a set and lattice theoretic methodology for image analysis, which aims at quantitatively describing the geometrical structure of im...

In this Letter, a new face recognition approach based on curvelets and local ternary patterns (LTP) is proposed. First, we observe that the curvelet transform is a new anisotropic multi-resolution transform and can efficiently represent edge discontinuities in face images, and that the LTP operator is one of the best texture descriptors in terms of characterizing face image details. This motiva...

This paper presents an approach for breast cancer diagnosis in digital mammogram using curvelet transform. After decomposing the mammogram images in curvelet basis, a special set of the biggest coefficients is extracted as feature vector. The Euclidean distance is then used to construct a supervised classifier. The experimental results gave a 98.59% classification accuracy rate, which indicate ...