Search results for "Pixel"

showing 10 items of 421 documents

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 Indeed, it represents one of the basic challenges, especially in case of historical documents analysis.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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New Cloud Detection Algorithm for Multispectral and Hyperspectral Images: Application to ENVISAT/MERIS and PROBA/CHRIS Sensors

2006

This work presents a new methodology that faces the problem of accurate identification of location and abundance of clouds in multispectral images acquired by space-borne sensors working in the visible and near-infrared (VNIR) spectral range. The amount of images acquired over the globe every day by the instruments on board Earth Observation satellites makes inevitable that many of these images present cloud covers. The objective of this work is to develop and validate a method that takes advantage of the high spectral and radiometric resolution, and the specific band locations (e.g. the oxygen band) of present multispectral sensors to increase the cloud detection accuracy. Moreover, the me…

Computer sciencebusiness.industryMultispectral imageHyperspectral imagingCloud computingSubpixel renderingVNIRRadiometryComputer visionArtificial intelligenceImage sensorbusinessImage resolutionAstrophysics::Galaxy AstrophysicsRemote sensing
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Segmentation of Hyperspectral Images for the Detection of Rotten Mandarins

2008

The detection of rotten citrus in packing lines is carried out manually under ultraviolet illumination, which is dangerous for workers. Light emitted by the rotten region of the fruit due to the ultraviolet-induced fluorescence is used by the operator to detect the damages. This procedure is required because the low contrast between the damaged and sound skin under visible illumination difficult their detection. We study a set of techniques aimed to detect rottenness in citrususing visible and near infrared lighting trough an hyperspectral imaging system. Methods for selecting a proper set of wavelengths are investigated such as correlation analysis, mutual information, stepwise or genetic …

Computer sciencebusiness.industryNear-infrared spectroscopyHyperspectral imagingPattern recognitionFeature selectionMutual informationImage segmentationLinear discriminant analysisComputer visionSegmentationArtificial intelligencePixel classificationbusiness
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Subpixel determination of imperfect circles characteristics

2008

This article deals with the problem of the determination of characteristics of imperfect circular objects in discrete images, namely the radius and center coordinates. To limit distortion, a multi-level method based on active contours was developed. Its originality is to furnish a set of geometric envelopes in one pass, with a correspondence between grayscale and a regularity scale. The adequacy of this approach was tested with several methods, among them is the Radon-based method. More particularly, this study indicates the relevance of the use of active contours combined with a Radon transform-based method which was improved using a fitting considering the discrete implementation of the R…

Computer sciencechemistry.chemical_elementRadonImage processingGeometryGeometric noise010103 numerical & computational mathematics02 engineering and technology01 natural sciencesGrayscaleEdge detectionArtificial IntelligenceDistortion[ INFO.INFO-TI ] Computer Science [cs]/Image Processing0202 electrical engineering electronic engineering information engineering0101 mathematicsComputingMilieux_MISCELLANEOUSRadon transformActive contour modelRadon transformActive contoursDiscrete circlesSubpixel renderingchemistry[INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV]Signal Processing020201 artificial intelligence & image processingComputer Vision and Pattern RecognitionModel fittingAlgorithmSoftware
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Breast Ultra-Sound image segmentation: an optimization approach based on super-pixels and high-level descriptors

2015

International audience; Breast cancer is the second most common cancer and the leading cause of cancer death among women. Medical imaging has become an indispensable tool for its diagnosis and follow up. During the last decade, the medical community has promoted to incorporate Ultra-Sound (US) screening as part of the standard routine. The main reason for using US imaging is its capability to differentiate benign from malignant masses, when compared to other imaging techniques. The increasing usage of US imaging encourages the development of Computer Aided Diagnosis (CAD) systems applied to Breast Ultra-Sound (BUS) images. However accurate delineations of the lesions and structures of the b…

ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONCAD02 engineering and technology[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processingBI-RADS lexiconOptimization based Segmentation030218 nuclear medicine & medical imaging03 medical and health sciences0302 clinical medicineBreast cancerCut0202 electrical engineering electronic engineering information engineeringMedical imagingMedicineComputer visionBreast ultrasound[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processingPixelmedicine.diagnostic_testbusiness.industryBreast Ultra-SoundGraph-CutsImage segmentationmedicine.disease3. Good healthComputingMethodologies_PATTERNRECOGNITIONComputer-aided diagnosis020201 artificial intelligence & image processingMachine-Learning based SegmentationArtificial intelligencebusiness[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing
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Interactive Pansharpening and Active Classification in Remote Sensing

2013

This chapter presents two multimodal prototypes for remote sensing image classification where user interaction is an important part of the system. The first one applies pansharpening techniques to fuse a panchromatic image and a multispectral image of the same scene to obtain a high resolution (HR) multispectral image. Once the HR image has been classified the user can interact with the system to select a class of interest. The pansharpening parameters are then modified to increase the system accuracy for the selected class without deteriorating the performance of the classifier on the other classes. The second prototype utilizes Bayesian modeling and inference to implement active learning …

ComputingMethodologies_PATTERNRECOGNITIONContextual image classificationKernel (image processing)PixelComputer scienceMultispectral imageComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONDecision boundaryLinear discriminant analysisClassifier (UML)Panchromatic filmRemote sensing
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Cloud screening and multitemporal unmixing of MERIS FR data

2007

The operational use of MERIS images can be hampered by the presence of clouds. This work presents a cloud screening algorithm that takes advantage of the high spectral and radiometric resolutions of MERIS and the specific location of some of its bands to increase the cloud detection accuracy. Moreover, the proposed algorithm provides a per-pixel probabilistic map of cloud abundance rather than a binary cloud presence flag. In order to test the proposed algorithm we propose a cloud screening validation method based on temporal series. In addition, we evaluate the impact of the cloud screening in a multitemporal unmixing application, where a temporal series of MERIS FR images acquired over Th…

ComputingMilieux_GENERALMERISLaboratory of Geo-information Science and Remote SensingCloud screeningMultispectral images550 - Earth sciencesLaboratorium voor Geo-informatiekunde en Remote SensingSub-pixel classificationPE&RCAstrophysics::Galaxy AstrophysicsSpectral unmixing
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Automated detection of patient movement during a CBCT scan based on the projection data.

2015

Objectives To develop an automated procedure to detect patient motion on the projection images acquired during a cone beam computed tomography (CBCT) scan and to evaluate the method's feasibility on small real-world CBCT images in relation to visual assessment. Methods Based on optical flow theory, software was developed using the sequence of the projection images of a CBCT machine for automated detection of patient motion. Averaged acceleration vectors were used as measurement data and compared with visual assessment of the projection images displayed as video. Seventy-nine CBCT data sets (small field-of-view: 40 mm) from our patient database were selected in a sequential fashion and evalu…

Cone beam computed tomographyComputer scienceMovementOptical flowVideo RecordingSensitivity and SpecificityPathology and Forensic MedicineAccelerationSoftwareImaging Three-DimensionalHumansRadiology Nuclear Medicine and imagingDentistry (miscellaneous)Computer visionSensitivity (control systems)Projection (set theory)Pixelbusiness.industryPhantoms ImagingFrame (networking)Cone-Beam Computed TomographyFeasibility StudiesRadiographic Image Interpretation Computer-AssistedSurgeryArtificial intelligenceOral SurgerybusinessArtifactsAlgorithmsSoftwareOral surgery, oral medicine, oral pathology and oral radiology
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Real-time image segmentation for anomalies detection using SVM approximation

2003

In this paper, we propose a method of implementation improvement of the decision rule of the support vector machine, applied to real-time image segmentation. We present very high speed decisions (approximately 10 ns per pixel) which can be useful for detection of anomalies on manufactured parts. We propose an original combination of classifiers allowing fast and robust classification applied to image segmentation. The SVM is used during a first step, pre-processing the training set and thus rejecting any ambiguities. The hyperrectangles-based learning algorithm is applied using the SVM classified training set. We show that the hyperrectangle method imitates the SVM method in terms of perfor…

Contextual image classificationPixelArtificial neural networkImage qualitybusiness.industryComputer scienceComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONScale-space segmentationPattern recognitionImage segmentationSupport vector machineHyperrectangleComputer visionArtificial intelligencebusinessSPIE Proceedings
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Cloud-screening algorithm for ENVISAT/MERIS multispectral images

2007

This paper presents a methodology for cloud screening of multispectral images acquired with the Medium Resolution Imaging Spectrometer (MERIS) instrument on-board the Environmental Satellite (ENVISAT). The method yields both a discrete cloud mask and a cloud-abundance product from MERIS level-lb data on a per-pixel basis. The cloud-screening method relies on the extraction of meaningful physical features (e.g., brightness and whiteness), which are combined with atmospheric-absorption features at specific MERIS-band locations (oxygen and watervapor absorptions) to increase the cloud-detection accuracy. All these features are inputs to an unsupervised classification algorithm; the cloud-proba…

Contextual image classificationPixelComputer sciencebusiness.industryMultispectral imageFeature extractionImaging spectrometer550 - Earth sciencesImage processingCloud computingSnowSpectral lineMultispectral pattern recognitionGeneral Earth and Planetary SciencesElectrical and Electronic EngineeringbusinessAstrophysics::Galaxy AstrophysicsWater vaporRemote sensing
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