Search results for "Transform"

showing 10 items of 3975 documents

Automated detection of microaneurysms using robust blob descriptors

2013

International audience; Microaneurysms (MAs) are among the first signs of diabetic retinopathy (DR) that can be seen as round dark-red structures in digital color fundus photographs of retina. In recent years, automated computer-aided detection and diagnosis (CAD) of MAs has attracted many researchers due to its low-cost and versatile nature. In this paper, the MA detection problem is modeled as finding interest points from a given image and several interest point descriptors are introduced and integrated with machine learning techniques to detect MAs. The proposed approach starts by applying a novel fundus image contrast enhancement technique using Singular Value Decomposition (SVD) of fun…

Computer scienceSVMComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION02 engineering and technologyFundus (eye)[ INFO.INFO-CV ] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]030218 nuclear medicine & medical imaging03 medical and health sciences0302 clinical medicine[INFO.INFO-CV] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]0202 electrical engineering electronic engineering information engineeringmedicineComputer visionRetinaRadon transformbusiness.industrySURFHessian[INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]Diabetic retinopathymedicine.diseaseMicroaneurysmSupport vector machinemedicine.anatomical_structureComputer-aided diagnosis020201 artificial intelligence & image processingArtificial intelligencebusinessSVDRetinopathy
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An Automatic HEp-2 Specimen Analysis System Based on an Active Contours Model and an SVM Classification

2019

The antinuclear antibody (ANA) test is widely used for screening, diagnosing, and monitoring of autoimmune diseases. The most common methods to determine ANA are indirect immunofluorescence (IIF), performed by human epithelial type 2 (HEp-2) cells, as substrate antigen. The evaluation of ANA consist an analysis of fluorescence intensity and staining patterns. This paper presents a complete and fully automatic system able to characterize IIF images. The fluorescence intensity classification was obtained by performing an image preprocessing phase and implementing a Support Vector Machines (SVM) classifier. The cells identification problem has been addressed by developing a flexible segmentati…

Computer scienceSVMKNN02 engineering and technologylcsh:TechnologyIIF imageHough transformlaw.inventionlcsh:Chemistry03 medical and health scienceslawClassifier (linguistics)0202 electrical engineering electronic engineering information engineeringPreprocessorGeneral Materials ScienceSegmentationcell segmentationlcsh:QH301-705.5InstrumentationIIF images030304 developmental biologyFluid Flow and Transfer Processes0303 health sciencesIndirect immunofluorescencelcsh:Tbusiness.industryProcess Chemistry and TechnologyGeneral EngineeringPattern recognitionSettore FIS/07 - Fisica Applicata(Beni Culturali Ambientali Biol.e Medicin)ROC curvelcsh:QC1-999Computer Science ApplicationsSupport vector machineParameter identification problemFluorescence intensityHough transformlcsh:Biology (General)lcsh:QD1-999lcsh:TA1-2040020201 artificial intelligence & image processingArtificial intelligencelcsh:Engineering (General). Civil engineering (General)businesslcsh:Physicsactive contours modelApplied Sciences
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Classification of Melanoma Lesions Using Sparse Coded Features and Random Forests

2016

International audience; Malignant melanoma is the most dangerous type of skin cancer, yet it is the most treatable kind of cancer, conditioned by its early diagnosis which is a challenging task for clinicians and dermatologists. In this regard, CAD systems based on machine learning and image processing techniques are developed to differentiate melanoma lesions from benign and dysplastic nevi using dermoscopic images. Generally, these frameworks are composed of sequential processes: pre-processing, segmentation, and classification. This architecture faces mainly two challenges: (i) each process is complex with the need to tune a set of parameters, and is specific to a given dataset; (ii) the…

Computer scienceSparse codingComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONScale-invariant feature transformImage processingDermoscopy02 engineering and technology[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing030218 nuclear medicine & medical imaging03 medical and health sciences0302 clinical medicineHistogram0202 electrical engineering electronic engineering information engineeringmedicineComputer visionSegmentationMelanoma[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processingbusiness.industryMelanomaCancerPattern recognitionImage segmentationSparse approximationRandom forestsmedicine.diseaseClassificationRandom forest020201 artificial intelligence & image processingArtificial intelligenceSkin cancerNeural codingbusiness[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing
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Morphological Analysis Combined with a Machine Learning Approach to Detect Utrasound Median Sagittal Sections for the Nuchal Translucency Measurement

2017

The screening of chromosomal defects, as trisomy 13, 18 and 21, can be obtained by the measurement of the nuchal translucency thickness scanning during the end of the first trimester of pregnancy. This contribution proposes an automatic methodology to detect mid-sagittal sections to identify the correct measurement of nuchal translucency. Wavelet analysis and neural network classifiers are the main strategies of the proposed methodology to detect the frontal components of the skull and the choroid plexus with the support of radial symmetry analysis. Real clinical ultrasound images were adopted to measure the performance and the robustness of the methodology, thus it can be highlighted an er…

Computer scienceSpeech recognition02 engineering and technologyWavelet analysi03 medical and health sciences0302 clinical medicineWaveletMid-sagittal section Neural network Nuchal translucency Symmetry transform Wavelet analysis.Nuchal translucencyRobustness (computer science)Nuchal Translucency Measurement0202 electrical engineering electronic engineering information engineeringmedicineMid-sagittal sectionSettore INF/01 - InformaticaArtificial neural networkbusiness.industrySymmetry transformPattern recognitionmedicine.diseaseNeural networkSagittal planemedicine.anatomical_structureNuchal translucencyMorphological analysis020201 artificial intelligence & image processingArtificial intelligenceTrisomybusiness030217 neurology & neurosurgery
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Tempo Induction from Music Recordings Using Ensemble Empirical Mode Decomposition Analysis

2011

Tempo and beat are among the most important features of Western music. Owing to the perceptual nature of tempo, its automatic analysis and extraction remains a difficult task for a large variety of music genres. Western music notation represents musical events using a hierarchical metrical structure distinguishing different time scales. This hierarchy is often modeled using three levels: the tatum, the tactus, and the measure. The tatum represents the shortest durational value in music that is not just an accidental phenomenon (Bilmes 1993). The tactus period is the most perceptually prominent period, and is the period at which most humans would tap their feet in time with the music (Lerdah…

Computer scienceSpeech recognitionmedia_common.quotation_subjectMusicalNotationHilbert–Huang transformComputer Science ApplicationsRhythmAudio editing softwarePerceptionMedia TechnologyMusic information retrievalBeat (music)Musicmedia_commonComputer Music Journal
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Uncalibrated Reconstruction: An Adaptation to Structured Light Vision

2003

Abstract Euclidean reconstruction from two uncalibrated stereoscopic views is achievable from the knowledge of geometrical constraints about the environment. Unfortunately, these constraints may be quite difficult to obtain. In this paper, we propose an approach based on structured lighting, which has the advantage of providing geometrical constraints independent of the scene geometry. Moreover, the use of structured light provides a unique solution to the tricky correspondence problem present in stereovision. The projection matrices are first computed by using a canonical representation, and a projective reconstruction is performed. Then, several constraints are generated from the image an…

Computer scienceStereoscopy02 engineering and technology[ INFO.INFO-CV ] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]01 natural scienceslaw.invention010309 optics[INFO.INFO-CV] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]Projection (mathematics)Artificial Intelligencelaw0103 physical sciencesEuclidean geometry0202 electrical engineering electronic engineering information engineeringComputer visionCorrespondence problemComputingMilieux_MISCELLANEOUSbusiness.industry[INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]Mobile robot navigationSignal Processing020201 artificial intelligence & image processingComputer Vision and Pattern RecognitionAffine transformationArtificial intelligencebusinessSoftwareStructured light
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An Improved Skew Angle Detection and Correction Technique for Historical Scanned Documents Using Morphological Skeleton and Progressive Probabilistic…

2017

International audience; Skew detection is a crucial step for document analysis systems. Indeed, it represents one of the basic challenges, especially in case of historical documents analysis. In this paper, we propose a novel robust skew angle detection and correction technique. Morphological Skeleton is introduced to significantly reduce the amount of data to treat by removing the redundant pixels and keeping only the central curves of the image components. The proposed method then uses Progressive Probabilistic Hough Transform (PPHT) to identify image lines. A special procedure is finally applied in order to estimate the global skew angle of the document image from these detected lines. E…

Computer science[SPI] Engineering Sciences [physics]ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONDocument image analysis02 engineering and technology01 natural sciencesElectronic mail[SPI]Engineering Sciences [physics]Robustness (computer science)HistogramOrientation0103 physical sciencesMorphological skeleton0202 electrical engineering electronic engineering information engineering010306 general physicsMorphological SkeletonProbabilistic hough transformPixelbusiness.industrySkewProbabilistic logicPattern recognitionProgressive Probabilistic Hough Transform[SPI.TRON] Engineering Sciences [physics]/Electronics[SPI.TRON]Engineering Sciences [physics]/ElectronicsSkew correctionAlgorithmImages020201 artificial intelligence & image processingArtificial intelligencebusinessSkew angle detection
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Fractional Fourier transform dual random phase encoding of time-varying signals

2008

Optical techniques have shown great potential in the field of information security to encode high-security images. Among several established methods, a double-random phase encryption technique (DRPE) for encoding a primary image into stationary white noise was developed by using the analogy between Fresnel diffraction patterns and the fractional Fourier transform (FrFT-DRPE). In this case, additional keys are obtained through the knowledge of the fractional orders of the FrFTs. In this work we propose an encoding setup for time-varying signals, mainly for short-haul fiber optics link applications, that can be considered as the temporal analogue of the spatial FrFT-DRPE. The behavior of the …

Computer sciencebusiness.industryBandwidth (signal processing)Phase (waves)White noiseEncryptionSignalAtomic and Molecular Physics and OpticsFractional Fourier transformElectronic Optical and Magnetic MaterialsOpticsEncoding (memory)Wigner distribution functionElectrical and Electronic EngineeringPhysical and Theoretical ChemistrybusinessFresnel diffractionOptics Communications
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Texture Classification with Generalized Fourier Descriptors in Dimensionality Reduction Context: An Overview Exploration

2008

In the context of texture classification, this article explores the capacity and the performance of some combinations of feature extraction, linear and nonlinear dimensionality reduction techniques and several kinds of classification methods. The performances are evaluated and compared in term of classification error. In order to test our texture classification protocol, the experiment carried out images from two different sources, the well known Brodatz database and our leaf texture images database.

Computer sciencebusiness.industryDimensionality reductionFeature extractionComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONNonlinear dimensionality reductionPattern recognitionContext (language use)Texture (geology)Term (time)symbols.namesakeFourier transformsymbolsArtificial intelligencebusiness
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Influence of the luminance spatial non-homogeneities of a display monitor on the contrast sensitivity function determination

1999

Abstract The application of computer devices equipped with video monitors both in clinical practice and human vision research has become widespread. These devices offer great advantages over other traditional methodologies (such as printed tests) because they facilitate the variation of the experimental parameters or the design of new psychophysical experiences. The aim of this paper is to determine the degree to which spatial inhomogeneity affects the generation of sinusoidal gratings on a video display. Knowing this degree of tolerance will enable us to determine the minimum demands that can be made on the graphic board and the video screens for their implementation in assessing contrast …

Computer sciencebusiness.industryFast Fourier transformFrequency spaceLuminanceGrayscaleHuman-Computer InteractionClinical PracticeHardware and ArchitecturePsychophysicsComputer visionSpatial frequencySensitivity (control systems)Artificial intelligenceElectrical and Electronic EngineeringbusinessDisplays
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