Medical image segmentation has become an essential technique in clinical and researchoriented applications. Because manual segmentation methods are tedious, and semi-automatic segmentation lacks the flexibility, fully-automatic methods have become the preferred type of medical image segmentation. This work proposes a robust fully automatic segmentation scheme based on the modified contouring te...

In order to solve the problem of rotation invariant texture image retrieval, an image retrieval algorithm based on Log-Polar and nonsubsampled contourlet transform (NSCT) is proposed. Log-Polar transform was first applied to texture image to convert the rotation to translation. Then, translation invariant NSCT was employed to decompose the transformed images. Standard deviations, energies and e...

Texture is a rich source of visual information about the surface characteristics of an object in the digital image. So texture characteristics play an important role in texture image classification. In this paper, we propose a novel approach of texture image classification based on nonsubsampled contourlet transform (NSCT) and local directional binary patterns (LDBP). The NSCT has translation i...

A complete texture image retrieval system includes two techniques: texture feature extraction and similarity measurement. Specifically, similarity measurement is a key problem for texture image retrieval study. In this paper, we present an effective similarity measurement formula. The MIT vision texture database, the Brodatz texture database, and the Outex texture database were used to verify t...

Multimodal medical image fusion plays a vital role in clinical diagnosis and treatment planning. In the image fusion methods based on nonsubsampled contourlet transform (NSCT) and pulse coupled neural network (PCNN), authors have used normalized coefficient value to motivate the PCNN-processing, which makes the fused image blurred, detail loss and decrease in contrast. In this paper, we present...