Search results for "processing"

Towards Risk-aware Access Control Framework for Healthcare Information Sharing

2018

High Level Modeling and Hardware Implementation of Image Processing Algorithms Using XSG

2019

International audience; Design of Systems-on-Chip has become very common especially with the remarkable advances in the field of high-level system modeling. In recent years, Matlab also offers a Simulink interface for the design of hardware systems. From a high-level specification, Matlab provides self-generation of HDL codes and/or FPGA configuration codes while providing other benefits of easy simulation. In addition, a large part of the Systems-on-Chip use at least one image processing algorithm and at the same time border detection is one of the most used algorithms. This paper presents a study and a hardware implementation of various algorithms of borders detection realized under Xilin…

An Introduction to Ontology Based Structured Knowledge Base System: Knowledge Acquisition Module

2013

The following text presents the method of supplementing and verifying information stored in a framework system of the semantic knowledge base. The indicated method refers to the knowledge of ontological character, in other words to information about definitions of concepts and relationships among them. The aim of the method is the constant supplementing and verifying of the knowledge, and making more precise and detailed information about existing connections between concepts. The key aspect of the method is questions generating strictly dependent on the preconceived structure of stored knowledge.

Depth sensing using coherence mapping

2010

A method for depth sensing based on sensing the visibility associated with the coherence function of a laser source is presented. The setup is based on an electronic speckle pattern interferometric (ESPI) setup, where the object depth is encoded into the amplitude of the interference pattern without the need for depth scanning. After performing phase-shifting method, the object three-dimensional (3-D) shape is reconstructed by means as a range image from the visibility of the image set of interferograms and where each gray level represents a given object depth. Experimental results validate the proposed approach for reflective diffuse objects at different measurement distances.

An Innovative Similarity Measure for Sentence Plagiarism Detection

2016

We propose and experimentally assess Semantic Word Error Rate (SWER), an innovative similarity measure for sentence plagiarism detection. SWER introduces a complex approach based on latent semantic analysis, which is capable of outperforming the accuracy of competitor methods in plagiarism detection. We provide principles and functionalities of SWER, and we complement our analytical contribution by means of a significant preliminary experimental analysis. Derived results are promising, and confirm to use the goodness of our proposal.

Randomized Hough Transform for Ellipse Detection with Result Clustering

2005

Our research is focused on the development of robust machine vision algorithms for pattern recognition. We want to provide robotic systems the ability to understand more on the external real world. In this paper, we describe a method for detecting ellipses in real world images using the randomized Hough transform with result clustering. A preprocessing phase is used in which real world images are transformed - noise reduction, greyscale transform, edge detection and final binarization - in order to be processed by the actual ellipse detector. The ellipse detector filters out false ellipses that may interfere with the final results. Due to the fact that usually more "virtual" ellipses are de…

Superresolving optical system with time multiplexing and computer decoding

2008

Objects that have slow temporal variations may be superresolved with two moving masks such as pinhole or grating. The first mask is responsible for encoding the input image, and the second one performs the decoding operation. This approach is efficient for exceeding the resolving capability beyond Abbe’s limit of resolution. However, the proposed setup requires two physical gratings that should move in a synchronized manner. We propose what is believed to be a novel configuration in which the second grating responsible for the information decoding is replaced with a detector array and some postprocessing digital procedures. In this way the synchronization problem that exists when two gratin…

Introducing the Concept of Hyperactivity in Multi Agent Systems

2013

International audience; Software Agents are no longer the simple communication gateways for devices to interconnect using one or more networks. With Multi Agent Systems contributing in a wide spectrum of intelligent systems, the Agents are in a more proactive role than just being responsible for passing messages between their respective base systems. Agent Relation Charts and the Hyperactive Transaction Model in general is one of the recent attempts of developing a multi-view design model for Multi Agent Systems. The model has made a clear distinction in the regular and intelligent activities of an agent. Based on these differences, the agents are classified into three main categories named…

SmartSpectra: Applying multispectral imaging to industrial environments

2005

SmartSpectra is a smart multispectral system for industrial, environmental, and commercial applications where the use of spectral information beyond the visible range is needed. The SmartSpectra system provides six spectral bands in the range 400-1000nm. The bands are configurable in terms of central wavelength and bandwidth by using electronic tunable filters. SmartSpectra consists of a multispectral sensor and the software that controls the system and simplifies the acquisition process. A first prototype called Autonomous Tunable Filter System is already available. This paper describes the SmartSpectra system, demonstrates its performance in the estimation of chlorophyll in plant leaves, …

Probing neural mechanisms of music perception, cognition, and performance using multivariate decoding.

2012

Recent neuroscience research has shown increasing use of multivariate decoding methods and machine learning. These methods, by uncovering the source and nature of informative variance in large data sets, invert the classical direction of inference that attempts to explain brain activity from mental state variables or stimulus features. However, these techniques are not yet commonly used among music researchers. In this position article, we introduce some key features of machine learning methods and review their use in the field of cognitive and behavioral neuroscience of music. We argue for the great potential of these methods in decoding multiple data types, specifically audio waveforms, e…