Search results for "multimodal images"

showing 2 items of 2 documents

Improving point matching on multimodal images using distance and orientation automatic filtering

2016

International audience; Speed Up Robust Features SURF is one of the most popular and efficient methods used for image registration task. In order to achieve a correct registration, a good matching of feature point is required. However in the case of multimodal images, the high and non-linear intensity changes between different modalities led to many outliers (mismatching of detected points) and consequently a fail in the registration. Therefore, in this paper we introduce an efficient method devoted to the detection and removal of such outlier. It's based on an automatic filtering of outliers on both distance and orientation between features points. We tested our proposed method on a set of…

HistogramsComputer scienceFeature extractionComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONImage registration02 engineering and technologyimage matchingfeature point matchingRANSACElectronic mailautomatic outlier filteringHistogramautomatic orientation filteringhigh-nonlinear intensity[ INFO.INFO-TI ] Computer Science [cs]/Image Processing0202 electrical engineering electronic engineering information engineeringautomatic distance filteringOutlier detectionComputer visionIR visible imagesRobustnessmultimodal imagesUV imagesImage registrationimage filteringMeasurementbusiness.industryFeature matchingSURF020206 networking & telecommunicationsPoint set registrationPattern recognitionDetectorsdetected point mismatchingcultural heritagefluorescence imagesElectronic mail[INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV]Outlierspeed-up robust featuresFeature extraction020201 artificial intelligence & image processingAnomaly detectionArtificial intelligencebusiness
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Multimodal Images Classification using Dense SURF, Spectral Information and Support Vector Machine

2019

International audience; The multimodal image classification is a challenging area of image processing which can be used to examine the wall painting in the cultural heritage domain. In such classification, a common space of representation is important. In this paper, we present a new method for multimodal representation learning, by using a pixel-wise feature descriptor named dense Speed Up Robust Features (SURF) combined with the spectral information carried by the pixel. For classification of extracted features we have used support vector machine (SVM). Our database was extracted from acquisition on cultural heritage wall paintings that contain four modalities UV, Visible, IRR and fluores…

Computer scienceComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONImage processing02 engineering and technologyImage (mathematics)0202 electrical engineering electronic engineering information engineeringFeature descriptorRepresentation (mathematics)Spectral informationSpeeded up robust features SURFGeneral Environmental SciencePixelbusiness.industry[INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]020206 networking & telecommunicationsPattern recognitionSVM classificationSupport vector machineCultural heritageMultimodal imagesCielab spaceDense features[INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV]General Earth and Planetary Sciences020201 artificial intelligence & image processingArtificial intelligencebusinessFeature learning
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