1st and 2nd FM generation 3D halftoning1 MICRON PIXELS133-MEGAPIXEL180 degree images1-bit matrix completion100 Hue test1/f noise108 Megapixel
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2D VIEWS2D DCT2.5D reconstruction2-d scale2D metrics2D to Hologram conversion2D-plus-depth video2D and 3D video2.5D PRINTING2D/3D imaging, high performance computing, imaging systems, efficient computations and storage2.5 D printing2D AND 3D CONVERTIBLE DISPLAY2.5D printing2AFC2.5D2D2D printing2D-TO-3D CONVERSION ARTIFACTS2-D barcodes
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3D image compression3D Digital Image Correlation3D Data Sources3D Halftoning3D camera3D-HEVC3D adaptive halftoning3D scene flow estimation3D connected tube model360-degree videos3D Video Communications3D Shape Indexing and Retrieval3D/4D DATA PROCESSING AND FILTERING3D EDUCATIONAL MATERIAL3D Tracking3D Range Data3D surface reproduction3D STACK3D Modeling3D TRANSFORMATION3D model3D Imaging3D compression360-degree Image360 IMAGING3D HALFTONING3D range scanning360° video3D Curvelet3ARRI footage3D depth sensing3D/2D Visuals3D modeling3D RECONSTRUCTION3D rigid transformations3D Vision3D Immersion3D digital halftoning360 degree images3D Range Data Compression3D capture3D scanning3D Mapping3D modelling3D recovery3D Printing3D Point Cloud3D affine transformation3D printing3D Communications360-degree content3D shape3D PRINTER3D/4D Scanning3D video3D-LUT360 degrees video360-degree art exhibition3D CAMERAS360-degree image projection3D stereo vision3D perception360 panorama3D Morphable Model360-degree images3D Object Detection3D MODEL3D PRINTING3D face alignment3D theater program listing3D Measurement3D DIGITIZATION METHOD FOR OIL PAINTINGS3D-shooting3D position measurement of people3D Telepresence3D Data Processing3D shape indexing and retrieval3D mesh3D-color perception3D display3D refinement3D video processing3D scene classification3D warping3D objects3D surface3D Saliency3D optical scans3D data processing360-degree video streaming3D depth-map360-video3D mapping and localization3D/4D Data Processing and Filtering360VR3DMM3D Compression and Encryption3D VISUALIZATION3D reconstruction3D Iterative Halftoning360° STEREO PANORAMAS3D MESH3D Lidar3D Scene Reconstruction3D-CNN3DSR3D communications360-degree video3DViewers3D displays360-degree3D MESHES3D Display3D Gaussian splatting3D Models3D Compression3D Computer Graphics3D object shape3D shape analysis360-deg quality assessment360-DEGREE IMAGE3D Video Conferencing3D Quality3D Image Processing3D RANGE IMAGING3d localization3-D RECONSTRUCTION3D MODELLING3D and 2D3D SCENE RECONSTRUCTION AND MODELING3D SHAPE INDEXING AND RETRIEVAL3D SALIENCY3D Meshes3D-human body detection3D recursive search3D Video3-T pixel3D print3D halftoning3D INTERACTION360° VIDEO3D audio3D imaging3D ACQUISITION ARCHITECTURE3D RECOVERY3D printer3D Print Appearance3D colour Digital Image Correlation3D digitization and dissemination3D localization and mapping3D range geometry3D/4D SCANNING3D localization3D-assisted features3D Scene Reconstruction and Modeling3D-Anisotropic smoothing3DCNN3D human-centered technologies3D point cloud3D projector3D mesh simplification35MM FILM DIGITIZATION3d video3D STIMULI3D IMAGE3D vision3D3D encoding3D surface structure based halftoning3D glasses3D COMPRESSION AND ENCRYPTION3D Reconstruction360-degree imaging3D Color Printing3D-printing3d3D Range Data Encoding3D USER INTERFACES3D TV360-Degree Video Technology3D PROFILE3D cinema and TV360x3D scene capture3-D SHAPE RECOVERY3d mapping360 Video3A ALGORITHMS3D-high efficiency video coding3D visual representation3D DISPLAY
Colorant fading defects in raster region of interest (ROI) are among the most common printing issues in electrophotographic printers. Colorant fading manifests as faint print or customer content and is usually caused by low-level ink/cartridge. This paper presents an accurate method to detect the colorant fading defects and classify the defects based on their severity. There are two modules for this method. The first module uses the SLIC super-pixel method to separate the raster ROI and extract the smooth super-pixels. We design a novel unsupervised clustering algorithm to automatically extract the three or four main colors from the smooth super-pixels. Unsupervised data clustering is an important problem that arises in many image processing applications. We propose a new approach to unsupervised data clustering called Data Inter-Distance MEdiated Clustering (DIDMEC). Our new method is based on analyzing the matrix of Euclidean distances between each pair of points in the data set. Based on three simple properties, we devise an approach that effectively yields the same accuracy as the K-Means algorithm but at a much lower computational cost for a moderate number of sample points. The second module extracts feature vectors for each main color clustered by DIDMEC to classify the colorant fading defects based on their severity.