In this paper, a computer-aided diagnostic (CAD) system for the diagnosis of benign and malignant liver tumors from computed tomography (CT) images is presented. Liver is segmented from abdominal CT images using adaptive threshold and morphological processing. Each suspicious tumor region is automatically extracted from the segmented liver using FCM technique and the textural information obtain...

In this paper, a novel feature extraction scheme is proposed, based on multiresolution fast discrete curvelet transform for computer-aided diagnosis of liver diseases. The liver is segmented from CT images using adaptive threshold detection and morphological processing. The suspected tumour region is extracted from the segmented liver using FCM clustering. The textural information obtained from...

The work being presented here describes a novel approach for human emotion recognition based on curvelet transform. Our approach of the emotion recognition is motivated by the fact that emotions expressed more obviously by the facial curves, hence the technique proficient in capturing the edge singularity as well as the curve singularities shall yield the better results i.e. curvelets. Curvelet...

All the time, there is a demand of High-Resolution (HR) images in electronic imaging applications. Super-Resolution (SR) is an approach used to restore High-Resolution (HR) image from one or more Low-Resolution (LR) images. The goal of SR is to extract the independent information from each LR image in that set and combine the information into a single high resolution (HR) image. The quality of ...

Denoising of Positron Emission Tomography (PET) images is a challenging task due to the inherent low signal-to-noise ratio (SNR) of the acquired data. A pre-processing denoising step may facilitate and improve the results of further steps such as segmentation, quantification or textural features characterization. Different recent denoising techniques have been introduced and most state-of-the-a...

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...

Motion blur can significantly degrade the quality of an image. The images become blurred due to camera movements, object movements or displacements of pixels. Deblurring of an image is done by processing an image through curvelet transform and removal of noise by median filter. Experimental results show that proposed deblurring technique and accuracy measurement using peak signal to noise ratio...

Current methods of fusing side-scan sonar images fail to tackle the issues shadow removal, preservation information from adjacent strip images, and maintenance image clarity contrast. To address these deficiencies, a novel curvelet-transform-based approach that integrates complementary attribute details is proposed. By capitalizing on multiple scales orientations curvelet transform its intricat...

A key challenge in the seismic imaging of reflectors using surface reflection data is the subsurface illumination produced by a given data set and for a given complexity of the background model (of wavespeeds). The imaging is described here by the generalized Radon transform. To address the illumination challenge and enable (accurate) local parameter estimation, we develop a method for partial ...

Barcode localization is the main challenge in developing an image-based barcode reading system. Bar codes are able to carry both explicit information and a database key, by encoding a series of characters or symbols. This paper deals with localization of European Article Number-13 (EAN-13) barcode in an image. A new approach for detecting and locating bar-codes is introduced here, which is base...