Search results for "image processing"
showing 10 items of 3285 documents
Writer identification for historical handwritten documents using a single feature extraction method
2020
International audience; With the growth of artificial intelligence techniques the problem of writer identification from historical documents has gained increased interest. It consists on knowing the identity of writers of these documents. This paper introduces our baseline system for writer identification, tested on a large dataset of latin historical manuscripts used in the ICDAR 2019 competition. The proposed system yielded the best results using Scale Invariant Feature Transform (SIFT) as a single feature extraction method, without any preprocessing stage. The system was compared against four teams who participated in the competition with different feature extraction methods: SRS-LBP, SI…
Hardware Computation of Moment Functions in a Silicon Retina Using Binary Patterns
2006
International audience; We present in this paper a method for implementing moment functions in a CMOS retina for shape recognition applications. The method is based on the use of binary patterns and it allows the computation of different moment functions such geometric and Zernike moments of any orders by an adequate choice of the binary patterns. The advantages of the method over other methods described in the literature is that it is particularly suitable for the design of a programmable retina circuit where moment functions of different orders are obtained by simply loading the correct binary patterns into the memory devices implemented on the circuit. The moment values computed by the m…
PTNet: An efficient and green data center network
2017
International audience; In recent years, data centers have witnessed an exponential growth for hosting hundreds of thousands of servers as well as to accommodating a very large demand for resources. To fulfill the required level of demand, some approaches tackled network aspects so to host a huge number of servers while others focused on delivering rapid services to the clients by minimizing the path length between any two servers. In general, network devices are often designed to achieve 1:1 oversubscription. Alternatively, in a realistic data center environment, the average utilization of a network could vary between 5% and 25%, and thus the energy consumed by idle devices is wasted. This…
Toward a virtual reconstruction of an antique three-dimensional marble puzzle
2017
International audience; Abstract | Introduction | Related Work | Acquisition Setup, Proposed Prototype: Calibration and Visibility | Preprocessing of Scanned Three-Dimensional Fragment Data | Processing of Scanned Three-Dimensional Surface Data: Matching | Conclusion and Future Works | Appendices | Acknowledgments | ReferencesAbstract. The reconstruction of broken objects is an important field of research for many applications, such as art restoration, surgery, forensics, and solving puzzles. In archaeology, the reconstruction of broken artifacts is a very time-consuming task due to the handling of fractured objects, which are generally fragile. However, it can now be supported by three-dim…
An Image Segmentation Algorithm based on Community Detection
2016
International audience; With the recent advances in complex networks, image segmentation becomes one of the most appropriate application areas. In this context, we propose in this paper a new perspective of image segmentation by applying two efficient community detection algorithms. By considering regions as communities, these methods can give an over-segmented image that has many small regions. So, the proposed algorithms are improved to automatically merge those neighboring regions agglomerative to achieve the highest modularity/stability. To produce sizable regions and detect homogeneous communities, we use the combination of a feature based on the Histogram of Oriented Gradients of the …
Adaptive Learning Process for the Evolution of Ontology-Described Classification Model in Big Data Context
2016
International audience; One of the biggest challenges in Big Data is to exploit value from large volumes of variable and changing data. For this, one must focus on analyzing the data in these Big Data sources and classify the data items according to a domain model (e.g. an ontology). To automatically classify unstructured text documents according to an ontology, a hierarchical multi-label classification process called Semantic HMC was proposed. This process uses ontologies to describe the classification model. To prevent cold start and user overload, the classification process automatically learns the ontology-described classification model from a very large set of unstructured text documen…
Automated Characterization of Mouth Activity for Stress and Anxiety Assessment
2016
International audience; Non-verbal information portrayed by human facial expression, apart from emotional cues also encompasses information relevant to psychophysical status. Mouth activities in particular have been found to correlate with signs of several conditions; depressed people smile less, while those in fatigue yawn more. In this paper, we present a semi-automated, robust and efficient algorithm for extracting mouth activity from video recordings based on Eigen-features and template-matching. The algorithm was evaluated for mouth openings and mouth deformations, on a minimum specification dataset of 640x480 resolution and 15 fps. The extracted features were the signals of mouth expa…
Comparative Study of the Mobile Learning Architectures
2016
International audience; With the emergence of mobile devices (Smart Phone, PDA, UMPC, game consoles, etc.), learning is changing from electronic learning (e-Learning) to mobile learning (m-learning). In fact, due to the mobility feature, it seems that the m-learning have to be adapted with the change within the context. Several researches addressed this issue and implemented a mobile learning environment to prove its usefulness and feasibility in various domains. In this article, we conduct a comparative study between a list of mobile learning architectures and methods that are presented in the literature. The performance of these architectures is evaluated based on several criteria, such a…
Privacy in Big Data
2016
International audience
Overlapping community detection versus ground-truth in AMAZON co-purchasing network
2015
International audience; Objective evaluation of community detection algorithms is a strategic issue. Indeed, we need to verify that the communities identified are actually the good ones. Moreover, it is necessary to compare results between two distinct algorithms to determine which is most effective. Classically, validations rely on clustering comparison measures or on quality metrics. Although, various traditional performance measures are used extensively. It appears very clearly that they cannot distinguish community structures with different topological properties. It is therefore necessary to propose an alternative methodology more sensitive to the community structure variations in orde…