Similarity measures for non-rigid multimodal registration are required to be local in order to enable correction of small image differences, and multimodal, to allow images to be acquired using different imaging techniques. Unfortunately all commonly used multimodal similarity measures are inherently global and cannot be directly used to estimate local image properties. We have derived a local ...

The use of biometrics in the field of enhancing security and authentication in sensitive systems is a rapidly evolving technology. The increasing attacks and decreasing security in unimodal systems have resulted in designing multimodal systems combining different biometric traits. A lot of research has already been done in designing multimodal systems with fusion at rank and match-score level u...

In this paper, we propose a novel learning based method for automated segmentation of brain tumor in multimodal MRI images. The machine learned features from fully convolutional neural network (FCN) and hand-designed texton features are used to classify the MRI image voxels. The score map with pixelwise predictions is used as a feature map which is learned from multimodal MRI training dataset u...

Single-sensor approaches to multimodal biometric authentication targeting the human hand in multiple-matcher scenarios provide higher security in terms of accuracy and resistance to biometric system attacks than unimodal systems. This paper introduces a novel multimodal hand biometric system using palmar images acquired by a commercially available flatbed scanner. Hence, the presented approach ...

Mutual information has been successfully used as an effective similarity measure for multimodal image registration. However, a drawback of the standard mutual information-based computation is that the joint histogram is only calculated from the correspondence between individual voxels in the two images. In this paper, the normalized mutual information measure is extended to consider the corresp...

Image registration is a fundamental problem that can be found in a diverse range of elds within the research community It is used in areas such as engineering science medicine robotics computer vision and image processing which often require the process of developing a spatial mapping between sets of data Registration plays a crucial role in the medical imaging eld where continual advances in i...

As the number of images grows rapidly on the Internet, the scalability of image retrieval systems becomes a significant issue. In this paper, we propose two distributed clustering algorithms to scale up the bag-ofvisual-words model on millions of images and billions of visual features by leveraging distributed systems. We also introduce a multimodal fusion model to utilize textual data to impro...

A wide range of semiotic resources has been used to construct meaning. Visual systems of meaning offer different resources and potentials for meaning making. Readers need to familiarize themselves with a variety of ways to make sense and read visual images. This paper, drawing on the theories of semiotics, art and visual communication grammar, presents a framework of interpretive strategies to ...

We present a CUDA implementation of a complete registration algorithm, which is capable of aligning two multimodal images, using affine linear transformations and normalized gradient fields. Through the extensive use of different memory types, well handled thread management and efficient hardware interpolation we gained fast executing code. Contrary to the common technique of reducing kernel ca...