Search results for "Computer Vision"

showing 10 items of 2353 documents

Image Segmentation based on Genetic Algorithms Combination

2005

The paper describes a new image segmentation algorithm called Combined Genetic segmentation which is based on a genetic algorithm. Here, the segmentation is considered as a clustering of pixels and a similarity function based on spatial and intensity pixel features is used. The proposed methodology starts from the assumption that an image segmentation problem can be treated as a Global Optimization Problem. The results of the image segmentations algorithm has been compared with recent existing techniques. Several experiments, performed on real images, show good performances of our approach compared to other existing methods.

Settore INF/01 - InformaticaComputer scienceSegmentation-based object categorizationbusiness.industryComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONScale-space segmentationImage segmentationReal imageGenetic Algorithms clusteringImage textureMinimum spanning tree-based segmentationRegion growingComputer Science::Computer Vision and Pattern RecognitionSegmentationComputer visionArtificial intelligenceCluster analysisbusiness
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A cooperating strategy for objects recognition

1999

The paper describes an object recognition system, based on the co-operation of several visual modules (early vision, object detector, and object recognizer). The system is active because the behavior of each module is tuned on the results given by other modules and by the internal models. This solution allows to detect inconsistencies and to generate a feedback process. The proposed strategy has shown good performance especially in case of complex scene analysis, and it has been included in the visual system of the DAISY robotics system. Experimental results on real data are also reported.

Settore INF/01 - InformaticaComputer sciencebusiness.industry3D single-object recognitionComputer ScienceProcess (computing)Cognitive neuroscience of visual object recognitionComputer visionRoboticsArtificial intelligencebusinessObject (computer science)Theoretical Computer Science
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Segmentation and feature extraction in capillaroscopic videos

2015

This contribution describes a method to select regions of interest as capillaries of the oral mucosa and to extract their main features useful for real diagnosis purposes. A discrete version of the wavelet transform has been adopted for segmenting the images coming from video sequences acquired by a prototype capillaroscopic, able to put in evidence the red blood flow. A set of proper characteristics is automatically computed for a correct evaluation of the peripheral microcirculation.

Settore INF/01 - InformaticaComputer sciencebusiness.industryFeature extractionComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONWavelet transformVideo sequenceSet (abstract data type)Oral capillaroscopic videos wavelet segmentation feature extractionPeripheral microcirculationComputer visionSegmentationArtificial intelligencebusiness
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Content Based Indexing of Image and Video Databases by Global and Shape Features

1996

Indexing and retrieval methods based on the image content are required to effectively use information from the large repositories of digital images and videos currently available. Both global (colour, texture, motion, etc.) and local (object shape, etc.) features are needed to perform a reliable content based retrieval. We present a method for automatic extraction of global image features, like colour and motion parameters, and their use for data restriction in video database querying. Further retrieval is therefore accomplished, in a restricted set of images, by shape feature (skeleton, local symmetry moments, correlation, etc.) local search. The proposed indexing methodology has been deve…

Settore INF/01 - InformaticaComputer sciencebusiness.industrySearch engine indexingComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONCBIR video indexing image analysisDigital imageAutomatic image annotationImage textureFeature (computer vision)Computer visionLocal search (optimization)Visual WordArtificial intelligencebusinessImage retrieval
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A memetic approach to discrete tomography from noisy projections

2010

Discrete tomography deals with the reconstruction of images from very few projections, which is, in the general case, an NP-hard problem. This paper describes a new memetic reconstruction algorithm. It generates a set of initial images by network flows, related to two of the input projections, and lets them evolve towards a possible solution, by using crossover and mutation. Switch and compactness operators improve the quality of the reconstructed images during each generation, while the selection of the best images addresses the evolution to an optimal result. One of the most important issues in discrete tomography is known as the stability problem and it is tackled here, in the case of no…

Settore INF/01 - InformaticaCrossoverComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONEvolutionary algorithmDiscrete tomographyReconstruction algorithmImage processingIterative reconstructionStability problemArtificial IntelligenceRobustness (computer science)Signal ProcessingMemetic algorithmComputer Vision and Pattern RecognitionDiscrete tomographyAlgorithmSoftwareEvolutionary reconstruction.MathematicsPattern Recognition
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Restoration of Vertical Line Scratches with a Distributed Genetic Algorithm

2006

This contribution approaches the problem of scratch restoration in old movies as a optimisation's problem. The functional based on the statistical properties of the image around the scratch is optimised using an ad-hoc genetic algorithm. Given the large amount of the computational time needed by genetic algorithms, a network of standard workstations with heterogeneous operating systems has been used. Each workstation in the network works on each scratch to perform the restoration, and a specific machine works as root node with the task of distributing jobs on the network and adding the outputted restored scratches back into the image.

Settore INF/01 - InformaticaWorkstationbusiness.industryComputer scienceNode (networking)Noise reductionRestoration Scratches Genetic Algorithmlaw.inventionTask (computing)lawScratchMotion estimationGenetic algorithmComputer visionArtificial intelligencebusinesscomputerImage restorationcomputer.programming_languageSeventh International Workshop on Computer Architecture for Machine Perception (CAMP'05)
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Improving Harris corner selection strategy

2011

This study describes a corner selection strategy based on the Harris approach. Corners are usually defined as interest points for which intensity variation in the principal directions is locally maximised, as response from a filter given by the linear combination of the determinant and the trace of the autocorrelation matrix. The Harris corner detector, in its original definition, is only rotationally invariant, but scale-invariant and affine-covariant extensions have been developed. As one of the main drawbacks, corner detector performances are influenced by two user-given parameters: the linear combination coefficient and the response filter threshold. The main idea of the authors' approa…

Settore INF/01 - Informaticabusiness.industryAutocorrelationDetectorCorner detectionGeometryScale invarianceEdge detectionAutocorrelation matrixComputer Vision and Pattern RecognitionArtificial intelligenceInvariant (mathematics)Linear combinationbusinessAlgorithmSoftwareMathematicsHarris corner detector
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Graph-based minimal path tracking in the skeleton of the retinal vascular network

2012

This paper presents a semi-automatic framework for minimal path tracking in the skeleton of the retinal vascular network. The method is based on the graph structure of the vessel network. The vascular network is represented based on the skeleton of the available segmented vessels and using an undirected graph. Significant points on the skeleton are considered nodes of the graph, while the edge of the graph is represented by the vessel segment linking two neighboring nodes. The graph is represented then in the form of a connectivity matrix, using a novel method for defining vertex connectivity. Dijkstra and Floyd-Warshall algorithms are applied for detection of minimal paths within the graph…

Settore INF/01 - Informaticabusiness.industryComputer sciencePath trackingGraph theoryImage segmentationGraph bandwidthRetinal Images Graphs Dijkstra Floyd-WarshallGraph (abstract data type)Computer visionArtificial intelligencebusinessBeta skeletonDijkstra's algorithmAlgorithmRandom geometric graphMathematicsofComputing_DISCRETEMATHEMATICS2012 25th IEEE International Symposium on Computer-Based Medical Systems (CBMS)
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Face Expression Recognition through Broken Symmetries

2008

Security systems, criminology, physical access control and man-machine interactions are examples of applications where recognition of human faces may be crucial. In the present paper a new signature, based on a measure of axial symmetry called DST, is proposed as a significant feature to analyze facial expressions. The measure of symmetry is an elaborate difference between the internal and external symmetry kernels of an object. The idea here is to use the evolution of the symmetry measure of a face over an ordered set of its sub-images. We claim that different evolutionary trends will represent different face expressions. The proposed signature has been tested on several face databases (ps…

Settore INF/01 - Informaticabusiness.industryComputer sciencePattern recognitionFacial recognition systemMeasure (mathematics)Face Expression RecognitionExpression (mathematics)SymmetryDigital signatureFace (geometry)Feature (machine learning)Computer visionArtificial intelligenceSymmetry (geometry)businessAxial symmetry
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Shape analysis for image retrieval

1994

The main aim of this paper is to describe a method for locating a subimage of a stored image that approximately matches a given query image. This matching can support naive users in accessing an image database according to image contents rather symbolic attributes. The query image can be either composed using painting tools or cuts out of an actual scanned image. Our method is based on the extraction of features from the query image and from the stored images. The following three steps are involved: (l) an ISODATA algorithm is applied to segment (into region) both the query image and the stored images; (2) the normalized moment and geometrica! features are computed from the segmented region…

Settore INF/01 - Informaticacomputer vision ISODATA graphical interface.
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