14 research outputs found
Fuzzy logic based approach for object feature tracking
This thesis introduces a novel technique for feature tracking in sequences of
greyscale images based on fuzzy logic. A versatile and modular methodology
for feature tracking using fuzzy sets and inference engines is presented.
Moreover, an extension of this methodology to perform the correct tracking
of multiple features is also presented.
To perform feature tracking three membership functions are initially
defined. A membership function related to the distinctive property of the feature
to be tracked. A membership function is related to the fact of considering
that the feature has smooth movement between each image sequence and a
membership function concerns its expected future location. Applying these
functions to the image pixels, the corresponding fuzzy sets are obtained and
then mathematically manipulated to serve as input to an inference engine.
Situations such as occlusion or detection failure of features are overcome
using estimated positions calculated using a motion model and a state vector
of the feature.
This methodology was previously applied to track a single feature identified
by the user. Several performance tests were conducted on sequences of
both synthetic and real images. Experimental results are presented, analysed
and discussed. Although this methodology could be applied directly to multiple
feature tracking, an extension of this methodology has been developed
within that purpose. In this new method, the processing sequence of each
feature is dynamic and hierarchical. Dynamic because this sequence can
change over time and hierarchical because features with higher priority will
be processed first. Thus, the process gives preference to features whose location
are easier to predict compared with features whose knowledge of their
behavior is less predictable. When this priority value becomes too low, the
feature will no longer tracked by the algorithm. To access the performance
of this new approach, sequences of images where several features specified
by the user are to be tracked were used.
In the final part of this work, conclusions drawn from this work as well as
the definition of some guidelines for future research are presented.Nesta tese é introduzida uma nova técnica de seguimento de pontos característicos de objectos em sequências de imagens em escala de cinzentos baseada em lógica difusa. É apresentada uma metodologia versátil e modular para o seguimento de objectos utilizando conjuntos difusos e motores de inferência. É também apresentada uma extensão desta metodologia para o correcto seguimento de múltiplos pontos característicos.
Para se realizar o seguimento são definidas inicialmente três funções de pertença. Uma função de pertença está relacionada com a propriedade distintiva do objecto que desejamos seguir, outra está relacionada com o facto de se considerar que o objecto tem uma movimentação suave entre cada imagem da sequência e outra função de pertença referente à sua previsível localização futura. Aplicando estas funções de pertença aos píxeis da imagem, obtêm-se os correspondentes conjuntos difusos, que serão manipulados matematicamente e servirão como entrada num motor de inferência. Situações como a oclusão ou falha na detecção dos pontos característicos são ultrapassadas utilizando posições estimadas calculadas a partir do modelo de movimento e a um vector de estados do objecto.
Esta metodologia foi inicialmente aplicada no seguimento de um objecto assinalado pelo utilizador. Foram realizados vários testes de desempenho em sequências de imagens sintéticas e também reais. Os resultados experimentais obtidos são apresentados, analisados e discutidos. Embora esta metodologia pudesse ser aplicada directamente ao seguimento de múltiplos pontos característicos, foi desenvolvida uma extensão desta metodologia para esse fim. Nesta nova metodologia a sequência de processamento de cada ponto característico é dinâmica e hierárquica. Dinâmica por ser variável ao longo do tempo e hierárquica por existir uma hierarquia de prioridades relativamente aos pontos característicos a serem seguidos e que determina a ordem pela qual esses pontos são processados. Desta forma, o processo dá preferência a pontos característicos cuja localização é mais fácil de prever comparativamente a pontos característicos cujo conhecimento do seu comportamento seja menos previsível. Quando esse valor de prioridade se torna demasiado baixo, esse ponto característico deixa de ser seguido pelo algoritmo. Para se observar o desempenho desta nova abordagem foram utilizadas sequências de imagens onde várias características indicadas pelo utilizador são seguidas.
Na parte final deste trabalho são apresentadas as conclusões resultantes a partir do desenvolvimento deste trabalho, bem como a definição de algumas linhas de investigação futura
A Historical Account of Types of Fuzzy Sets and Their Relationships
In this paper, we review the definition and basic properties of the different types of fuzzy sets that have appeared up to now in the literature. We also analyze the relationships between them and enumerate some of the applications in which they have been used
Fuzzy Sets, Fuzzy Logic and Their Applications
The present book contains 20 articles collected from amongst the 53 total submitted manuscripts for the Special Issue “Fuzzy Sets, Fuzzy Loigic and Their Applications” of the MDPI journal Mathematics. The articles, which appear in the book in the series in which they were accepted, published in Volumes 7 (2019) and 8 (2020) of the journal, cover a wide range of topics connected to the theory and applications of fuzzy systems and their extensions and generalizations. This range includes, among others, management of the uncertainty in a fuzzy environment; fuzzy assessment methods of human-machine performance; fuzzy graphs; fuzzy topological and convergence spaces; bipolar fuzzy relations; type-2 fuzzy; and intuitionistic, interval-valued, complex, picture, and Pythagorean fuzzy sets, soft sets and algebras, etc. The applications presented are oriented to finance, fuzzy analytic hierarchy, green supply chain industries, smart health practice, and hotel selection. This wide range of topics makes the book interesting for all those working in the wider area of Fuzzy sets and systems and of fuzzy logic and for those who have the proper mathematical background who wish to become familiar with recent advances in fuzzy mathematics, which has entered to almost all sectors of human life and activity
Design of a Multi-biometric Platform, based on physical traits and physiological measures: Face, Iris, Ear, ECG and EEG
Security and safety is one the main concerns both for governments and for private
companies in the last years so raising growing interests and investments in
the area of biometric recognition and video surveillance, especially after the sad
happenings of September 2001. Outlays assessments of the U.S. government for
the years 2001-2005 estimate that the homeland security spending climbed from
100 billion of 2005. In this lapse of
time, new pattern recognition techniques have been developed and, even more
important, new biometric traits have been investigated and refined; besides
the well-known physical and behavioral characteristics, also physiological measures
have been studied, so providing more features to enhance discrimination
capabilities of individuals. This dissertation proposes the design of a multimodal
biometric platform, FAIRY, based on the following biometric traits: ear,
face, iris EEG and ECG signals. In the thesis the modular architecture of the
platform has been presented, together with the results obtained for the solution
to the recognition problems related to the different biometrics and their possible
fusion. Finally, an analysis of the pattern recognition issues concerning the
area of videosurveillance has been discussed
Design of a Multi-biometric Platform, based on physical traits and physiological measures: Face, Iris, Ear, ECG and EEG
Security and safety is one the main concerns both for governments and for private
companies in the last years so raising growing interests and investments in
the area of biometric recognition and video surveillance, especially after the sad
happenings of September 2001. Outlays assessments of the U.S. government for
the years 2001-2005 estimate that the homeland security spending climbed from
100 billion of 2005. In this lapse of
time, new pattern recognition techniques have been developed and, even more
important, new biometric traits have been investigated and refined; besides
the well-known physical and behavioral characteristics, also physiological measures
have been studied, so providing more features to enhance discrimination
capabilities of individuals. This dissertation proposes the design of a multimodal
biometric platform, FAIRY, based on the following biometric traits: ear,
face, iris EEG and ECG signals. In the thesis the modular architecture of the
platform has been presented, together with the results obtained for the solution
to the recognition problems related to the different biometrics and their possible
fusion. Finally, an analysis of the pattern recognition issues concerning the
area of videosurveillance has been discussed
Fuzzy Techniques for Decision Making 2018
Zadeh's fuzzy set theory incorporates the impreciseness of data and evaluations, by imputting the degrees by which each object belongs to a set. Its success fostered theories that codify the subjectivity, uncertainty, imprecision, or roughness of the evaluations. Their rationale is to produce new flexible methodologies in order to model a variety of concrete decision problems more realistically. This Special Issue garners contributions addressing novel tools, techniques and methodologies for decision making (inclusive of both individual and group, single- or multi-criteria decision making) in the context of these theories. It contains 38 research articles that contribute to a variety of setups that combine fuzziness, hesitancy, roughness, covering sets, and linguistic approaches. Their ranges vary from fundamental or technical to applied approaches
Proceedings of the Scientific-Practical Conference "Research and Development - 2016"
talent management; sensor arrays; automatic speech recognition; dry separation technology; oil production; oil waste; laser technolog
Proceedings of the Scientific-Practical Conference "Research and Development - 2016"
talent management; sensor arrays; automatic speech recognition; dry separation technology; oil production; oil waste; laser technolog