Human face detection is an indispensable component in face processing applications, including automatic face recognition, security surveillance, facial expression recognition, and the like. This paper presents a profile face detection algorithm based on curvelet features, as curvelet transform offers good directional representation and can capture edge information in human face from different a...

The information from patient’s body is captured as medical images and is used for surgical and diagnostic purposes. Compression of medical images is essential for storage and transmission of patient's data. Due to high impact of details in medical images, lossless compression is preferred. This paper presents colour medical image compression using Curvelet transform with lifting and Huffman cod...

For the ultrasound images accurate segmentation problem, this paper proposes a novel SVM semi-supervised segmentation method based on major features in curvelet domain. Firstly, ultrasound images were decomposed into different directions and frequencies in the curvelet domain, then the cauchy model was used to simulate curvelet coefficients distribution, thus the main distribution of the curvel...

Colour images are being used in many fields of research. One of the major issues of these types of colour images is their poor perception. A new method to enhance the colour image which using the concept of curvelet and multi structure decomposition. The proposed enhancement technique uses DCT (Discrete Curvelet Transform) to decomposed input image into different sub bands. Multi Structure (Mor...

This paper provides a comparative study of the performance of different Transform Domain filters like Wavelet, Contourlet, Bandelet and Curvelet with Firefly Algorithm (FA) applied to despeckle Synthetic Aperture Radar (SAR) images. Initially the feature enhancement and edge detection of speckled SAR image are integrated with improved gain function by shrinking and stretching the Wavelet Co-eff...

this paper presents a new procedure for automatic extraction of the blood vessels and optic disk (od) in fundus fluorescein angiogram (ffa). in order to extract blood vessel centerlines, the algorithm of vessel extraction starts with the analysis of directional images resulting from sub‑bands of fast discrete curvelet transform (fdct) in the similar directions and different scales. for this pur...

Tracking object from video sequences has become a very popular problem in the field of computer vision. Many algorithms have been proposed to solve this problem. Combined with the energy of curvelet coefficients and Kalman filter method, a new object tracking algorithm is proposed based on fast discrete curvelet transform. Firstly, this algorithm is initialized with the establishment of a movin...

This paper identifies two novel techniques for face features extraction based on two different multi-resolution analysis tools; the first called curvelet transform while the second is waveatom transform. The resultant features are trained and tested via three improved hidden Markov Model (HMM) classifiers, such as: Structural HMM (SHMM), Deviance Information CriterionInverse Weighted Average K-...

Face Biometrics is a science of automatically identifying individuals based on their unique facial features. The paper presents neural network classifier(Radial Basis Function Network) to detect frontal views of faces. The curvelet transform, Linear Discriminant Analysis(LDA) are used to extract features from facial images first, and Radial Basis Function Network(RBFN) is used to classify the f...