Multimodal segmentation, like the physicians in practice, uses several images, representing different features of the object under investigation, to make segmentation decisions. In this paper, a multimodal twodimensional segmentation method is introduced. The principle of this method is the combination of multimodal region growing and multimodal edge detection. The combining condition is univer...

Existing algorithms based on scale invariant feature transform (SIFT) and Harris corners such as edge-driven dual-bootstrap iterative closest point and Harris-partial intensity invariant feature descriptor (PIIFD) respectivley have been shown to be robust in registering multimodal retinal images. However, they fail to register color retinal images with other modalities in the presence of large ...

In this paper, the acquisition and content of a new homologous multimodal biometric database are presented. The SDUMLA-HMT database consists of face images from 7 view angles, finger vein images of 6 fingers, gait videos from 6 view angles, iris images from an iris sensor, and fingerprint images acquired with 5 different sensors. The database includes real multimodal data from 106 individuals. ...

We propose algorithm for local image difference measurement for multimodal image data based on value of mutual information of both images. Algorithm works with registered gray-level images. Similarity measure takes into account entropy of compared images. Results of proposed algorithm can be used for image comparison and better difference localization. Introduction Multimodal data sets are nowa...

Nowadays, as cameras are rapidly adopted in our daily routine, images of documents becoming both abundant and prevalent. Unlike natural that capture physical objects, document-images contain a significant amount text with critical semantics complicated layouts. In this work, we devise generic unsupervised technique to learn multimodal affinities between textual entities document-image, consider...