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...

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...

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...

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 ...

Malayalam, the official language of Kerala, a southern state of India has been accorded the honour of language of eminence. Hence the researches in recognition and related works in Malayalam language is gaining more prominence in the current scenario. This paper proposes the use of Curvelet transform and neural network for the recognition of handwritten Malayalam character. Curvelet transform i...

Denoising of real world images that are degraded by Gaussian noise is a long established problem in statistical signal processing. The existing models in time-frequency domain typically model the wavelet coefficients as either independent or jointly Gaussian. However, in the compression arena, techniques like denoising and detection, states the need for models to be nonGaussian in nature. Proba...

Malayalam, the official language of Kerala, a southern state of India has been accorded the honour of language of eminence. Hence the researches in recognition and related works in Malayalam language is gaining more prominence in the current scenario. This paper proposes the use of Curvelet transform and neural network for the recognition of handwritten Malayalam character. Curvelet transform i...

We present variants of both the digital curvelet transform, and the digital wave atom transform, which handle the image boundaries by mirror extension. Previous versions of these transforms treated image boundaries by periodization. The main ideas of the modifications are 1) to tile the discrete cosine domain instead of the discrete Fourier domain, and 2) to adequately reorganize the in-tile da...