Florent Duculty

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This paper presents a new measure which takes into accounts simultaneously brightness and connectivity, in the segmentation step, for crack detection on road pavement images. Features which are calculated along every free-form paths provide detection of cracks with any form and any orientation. The method proposed does not need learning stage of free defect(More)
Road distress needs to be detected early to optimize road maintenance cost; automatic survey of road distress is a big challenge, particularity for the detection of tiny cracks due to important variation of pavement textures. This paper presents a new method for crack detection by finding the minimal path passing on each pixel of image from every path with(More)
Prediction of physical particular phenomenon is based on knowledge of the phenomenon. This knowledge helps us to conceptualize this phenomenon around different models. Hidden Markov Models (HMM) can be used for modeling complex processes. This kind of models is used as tool for fault diagnosis systems. Nowadays, industrial robots living in stochastic(More)
This paper deals with a tool which may help maintenance manager to schedule maintenance activities. To help him, we show that by using events which can be observed on a process, like maintenance events, we can predict failures before they occur. Principles are based on the hypothesis that failure is preceded by a typical sequence of events. We also show(More)
Automatic pavement cracking detection is a part of road maintenance and rehabilitation strategies. Cracks detection is one of the main features used by road authorities to manage efficiently its networks. Different systems are available to perform road analysis. We give a short description of some of them. Apparatus which was used to provide our images is(More)
In this paper, we wish to find a minimal data size in order to better conceptualize industrial maintenance activities. We based our study on data given by a Synthetic Hidden Markov Model. This synthetic model is intended to produce real industrial maintenance observations (or “symbols”), with a corresponding degradation indicator. These time series events(More)
Prediction of physical particular phenomenon is based on knowledges of the phenomenon. Theses knowledges help us to conceptualize this phenomenon throw different models. Hidden Markov Models (HMM) can be used for modeling complex processes. We use this kind of models as tool for fault diagnosis systems. Nowadays, industrial robots living in stochastic(More)