Bytecode unification of geospatial computable models

Geospatial modelling revolves around the structures of data and the semantics of these structures. This is enough in simple cases, but becomes insufficient when the best structure and semantics is hard to find or the solution is too heterogeneous to fix and reuse. Field-based and objects-based geospatial models often share common GIS data structures interchangeably, but their all possible meanings are too many to define in an immutable manner. Less studied approach to geospatial modelling is using mutable structural properties and their semantic interpretation. This work shows that the functional aspect of geospatial models is just as important as the structural and semantic aspects. It also shows that semantic and even structural properties may change when functionality is integral part of the data model, and not exclusively separated at software implementation level. The paper uses this modelling paradigm to address the divide caused by field-based and object-based data models, and other challenges regarding synergy of geospatial systems that need to use both types of data models

Registration and Fusion of the Autofluorescent and Infrared Retinal Images

This article deals with registration and fusion of multimodal opththalmologic images obtained by means of a laser scanning device (Heidelberg retina angiograph). The registration framework has been designed and tested for combination of autofluorescent and infrared images. This process is a necessary step for consecutive pixel level fusion and analysis utilizing information from both modalities. Two fusion methods are presented and compared

Retrospective Illumination Correction of Retinal Images

A method for correction of nonhomogenous illumination based on optimization of parameters of B-spline shading model with respect to Shannon's entropy is presented. The evaluation of Shannon's entropy is based on Parzen windowing method (Mangin, 2000) with the spline-based shading model. This allows us to express the derivatives of the entropy criterion analytically, which enables efficient use of gradient-based optimization algorithms. Seven different gradient- and nongradient-based optimization algorithms were initially tested on a set of 40 simulated retinal images, generated by a model of the respective image acquisition system. Among the tested optimizers, the gradient-based optimizer with varying step has shown to have the fastest convergence while providing the best precision. The final algorithm proved to be able of suppressing approximately 70% of the artificially introduced non-homogenous illumination. To assess the practical utility of the method, it was qualitatively tested on a set of 336 real retinal images; it proved the ability of eliminating the illumination inhomogeneity substantially in most of cases. The application field of this method is especially in preprocessing of retinal images, as preparation for reliable segmentation or registration

Computer-aided Document Indexing System

An enormous number of documents is being produced that have to be stored, searched and accessed. Document indexing represents an efficient way to tackle this problem. Contributing to the document indexing process, we developed the Computer-Aided Document Indexing System (CADIS) that applies controlled vocabulary keywords from the EUROVOC thesaurus. The main contribution of this paper is the introduction of the special CADIS internal data structure that copes with the morphological complexity of the Croatian language. CADIS internal data structure ensures efficient statistical analysis of input documents and quick visual feedback generation that helps indexing documents more quickly, accurately and uniformly than by manual indexing