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Nowe klasy inteligentnych systemów interpretacji danych obrazowych. Systemy UBIAS

Ogiela M. R., Tadeusiewicz R.

Pomiary Automatyka Kontrola

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2010

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R. 56, nr 2

193-196

PL

W pracy opisano nową klasę specjalistycznych systemów informacyjnych, nazwanych UBIAS. Systemy takie należą do klasy kognitywnych systemów wnioskujących i są przeznaczone do znaczeniowej analizy skomplikowanych elementów nowoczesnych multimedialnych baz danych. Systemy UBIAS nadają się zwłaszcza do wydobywania znaczeniowej warstwy z informacji przedstawionej w postaci obrazów. W pracy przedstawiane są argumenty uzasadniające twierdzenie, że znaczenie obrazu i jego forma to dwa rozłączne aspekty, z których ten pierwszy jest zdecydowanie ważniejszy. Przedstawiane rozważania prowadzone są w sposób ogólny, ale eksperymenty, które doprowadziły do zdefiniowania systemów UBIAS odwoływały się w większości do semantycznej analizy obrazów biomedycznych.

EN

Paper describes new class of cognitive information systems named UBIAS (Understanding-Based Image Analysis Systems). Such systems belong to the group of cognitive reasoning computer systems and are dedicated for the semantic analysis of the images. In contemporary information systems many types of multimedial (e.g. visual) patterns are used, and semantic oriented analysis of such type of information is necessary. The general idea of automatic understanding of the images can be applied to any type of image, but in paper only biomedical images are taken into account. For diagnostic purposes and for intelligent selection of proper medical images from the big and not annotated databases (e.g., Internet) we must consider semantic content of the images, because reasoning based on image information as well as selection suitable image information needs semantic analysis of the image merit content. Typical image processing, analysis and also pattern recognition or clustering is definitely not satisfied. For automatic image understanding we propose UBIAS systems. Such systems are predecessors of a new generation of intelligent systems for understanding of visual data and using this data in many purposes. Possible applications spread out from medical diagnosis, throw searching in visual databases up to extraction biometric characteristics for personal identification. Additionally such systems are very useful in the tasks of intelligent semantic i.e. based on merit content (and not only with regard to the form), information management in multimedia databases. Particular systems dedicated to semantic analysis of the images were described in previous authors papers, but the presented paper present the class of UBIAS systems using general description instead of examples.

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Nowe klasy inteligentnych systemów interpretacji danych obrazowych. Systemy E-UBIAS

Ogiela M. R., Tadeusiewicz R.

Pomiary Automatyka Kontrola

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2010

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R. 56, nr 3

283-286

PL

Systemy UBIAS, opisywane we wcześniejszych pracach, zapoczątkowały powstanie nowej generacji inteligentnych systemów rozumienia danych obrazowych, w szczególności medycznych. Systemy te są również przydatne przy operowaniu w multimedialnych bazach danych ilekroć wykonywane operacje (wyszukiwania, grupowania, raportowania) muszą być oparte na merytorycznym sensie zawartości obrazu, a nie na formie informacji obrazowej. Systemy E-UBIAS przedstawiane w niniejszej pracy stanowią nową kategorię kognitywnych systemów przystosowanych do semantycznej interpretacji obrazu. Innowacją wprowadzoną w systemach E-UBIAS i poszerzającą możliwości wcześniejszych systemów UBIAS jest wprowadzenie nowego elementu zdobywania wiedzy podczas normalnej eksploatacji systemu (czyli swoistego procesu uczenia). Wskazano na możliwości zastosowania tych systemów, a także na nowe możliwości ich wykorzystania do pozyskiwania danych obrazowych traktowanych jako charakterystyki biometryczne.

EN

In previous papers given by authors the special class of computer vision systems was introduced and discussed. Such system named UBIAS was dedicated to cognitive analysis of images - especially medical ones. Replacing in UBIAS systems the image analysis and pattern recognition processes by cognitive resonance and automatic understanding we in fact introduce new class of vision systems which possibilities and advantages are not fully recognized until yet. Nevertheless the UBIAS image understanding systems have limitations related to "hand made" knowledge acquisition and representation process, which is necessary before starting the UBIAS system functioning. Sometimes collection of rules given by expert is too narrow, sometimes presentation of such rules in linguistic form used in UBIAS system is difficult, sometimes there are also another sources of problem - result is the same: The efficiency and quality of understanding of the images under consideration is not satisfactory. In all cases, when automatic understanding of the image using UBIAS methods is not good enough the solution can be E-UBIAS (Extended Understand-ing-Based Image Analysis System), which is presented in this article. The E-UBIAS systems set a new category of intelligent vision systems, which extend the possibilities of UBIAS towards acquiring knowledge and learning processes. In E-UBIAS systems two types of knowledge are used as a support of cognitive resonance procedures, leading to automatic understanding of the image semantic content. First type knowledge is acquired from experts ad is represented in linguistic form in graph-grammar structures used in typical cognitive resonance process. This is deductive part of the system. Second type knowledge is registered during normal work of the system. Every reasoning process performed by the system for some particular image give us new piece of information, which can be concatenated with other similar pieces coming from previous experiences. Such part of system is inductive one. Moreover systems belonging to the E-UBIAS class can be also used for collection of biometric characteristics for every person, which image was analyzed by the system and which semantic description was processed for automatic understanding purposes. It can be very useful in many security applications.

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Reconciling inconsistent profiles of agents' knowledge states in distributed multiagent systems using consensus methods

Katarzyniak R. P., Nguyen N. T.

Systems Science

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2000

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Vol. 26, nr 4

93-119

EN

In this paper, a partial model of a multiagent system is presented. This multiagent system is built of agents that use consensus methods to construct and update their knowledge of recognizable world states. Each agent in this system encapsulates a private database containing representations of empirically verified parts of knowledge of experienced world states (so-called encapsulated world profiles). In each agent and for each object of the world, this knowledge is computed by the agent as the consensus of encapsulated update resources. These update resources consist of the agent's perceptions of the object and similar perceptions communicated to the agent by other members of the same multiagent population. An example of encapsulated update resources is given and a list of related requirements for consensus computation is discussed.