1st and 2nd FM generation 3D halftoning1 MICRON PIXELS133-MEGAPIXEL180 degree images1-bit matrix completion100 Hue test108 Megapixel1/f noise
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2D VIEWS2D DCT2.5D reconstruction2D metrics2-d scale2D 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 printing2AFC2D2.5D2D printing2D-TO-3D CONVERSION ARTIFACTS2-D barcodes
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3D Data Sources3D Halftoning3D camera3D-HEVC3D adaptive halftoning3D image compression3D Digital Image Correlation3D EDUCATIONAL MATERIAL3D Tracking3D connected tube model3D scene flow estimation360-degree videos3D Video Communications3D/4D DATA PROCESSING AND FILTERING3D Shape Indexing and Retrieval3D STACK3D Modeling3D Range Data3D surface reproduction360-degree Image3D TRANSFORMATION3D model3D Imaging3D compression3D range scanning360° video3ARRI footage3D Curvelet3D depth sensing360 IMAGING3D HALFTONING3D RECONSTRUCTION3D rigid transformations3D Immersion3D Vision3D digital halftoning3D/2D Visuals3D modeling3D recovery3D Printing3D Point Cloud3D affine transformation360 degree images3D Range Data Compression3D capture3D scanning3D Mapping3D modelling3D shape3D PRINTER3D printing3D Communications360-degree content360 degrees video360-degree art exhibition3D CAMERAS360-degree image projection3D stereo vision3D perception360 panorama3D/4D Scanning3D-LUT3D video3D MODEL3D face alignment3D PRINTING3D Morphable Model360-degree images3D Object Detection3D DIGITIZATION METHOD FOR OIL PAINTINGS3D-shooting3D position measurement of people3D Telepresence3D Data Processing3D theater program listing3D Measurement3D display3D-color perception3D refinement3D shape indexing and retrieval3D mesh3D warping3D objects3D video processing3D scene classification3D optical scans3D data processing3D surface3D Saliency3D depth-map360-degree video streaming360-video360VR3D/4D Data Processing and Filtering3D mapping and localization3D reconstruction3DMM3D VISUALIZATION3D Compression and Encryption3D Scene Reconstruction3D Lidar3D-CNN3D Iterative Halftoning360° STEREO PANORAMAS3D MESH3D communications360-degree video3D displays3DSR3D Gaussian splatting360-degree3D Display3D MESHES3D Models3D Computer Graphics3D Compression3D object shape3D Image Processing3D RANGE IMAGING3d localization3-D RECONSTRUCTION3D MODELLING3D shape analysis360-deg quality assessment360-DEGREE IMAGE3D Quality3D Video Conferencing3D SHAPE INDEXING AND RETRIEVAL3D and 2D3D SCENE RECONSTRUCTION AND MODELING3D recursive search3D-human body detection3D Video3-T pixel3D print3D halftoning3D Meshes3D SALIENCY360° VIDEO3D INTERACTION3D imaging3D audio3D ACQUISITION ARCHITECTURE3D RECOVERY3D printer3D range geometry3D Print Appearance3D colour Digital Image Correlation3D digitization and dissemination3D localization and mapping3D-assisted features3D/4D SCANNING3D localization3D projector35MM FILM DIGITIZATION3D mesh simplification3D Scene Reconstruction and Modeling3D-Anisotropic smoothing3DCNN3D human-centered technologies3D point cloud3D vision3D encoding3D3D surface structure based halftoning3D COMPRESSION AND ENCRYPTION3D glasses3d video3D STIMULI3D IMAGE3D-printing3d3D Range Data Encoding3D Reconstruction360-degree imaging3D Color Printing3D TV360-Degree Video Technology3D PROFILE3D cinema and TV3D USER INTERFACES3D-high efficiency video coding3D visual representation3D DISPLAY3-D SHAPE RECOVERY360x3D scene capture3d mapping360 Video3A ALGORITHMS
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.