180 degree images1-bit matrix completion108 Megapixel1/f noise100 Hue test1st and 2nd FM generation 3D halftoning133-MEGAPIXEL1 MICRON PIXELS
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2D AND 3D CONVERTIBLE DISPLAY2.5D printing2x2 On-chip Lens2D/3D imaging, high performance computing, imaging systems, efficient computations and storage2.5D PRINTING2.5 D printing2D printing2-D barcodes2D-TO-3D CONVERSION ARTIFACTS2AFC2D2.5D2D VIEWS2D DCT2.5D reconstruction2D-plus-depth video2D and 3D video2D metrics2-d scale2D to Hologram conversion
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3d localization3-D RECONSTRUCTION3D MODELLING3D Image Processing3D RANGE IMAGING3D Video Conferencing3D Quality3D shape analysis360-deg quality assessment360-DEGREE IMAGE3D Compression3D Computer Graphics3D object shape3D Models3D print3D halftoning3D-human body detection3D recursive search3D Video3-T pixel3D Meshes3D SALIENCY3D SHAPE INDEXING AND RETRIEVAL3D SCENE RECONSTRUCTION AND MODELING3D and 2D3D-CNN3D Scene Reconstruction3D Lidar3D Iterative Halftoning360° STEREO PANORAMAS3D MESH3D reconstruction3DMM3D Compression and Encryption3D VISUALIZATION3D Gaussian splatting360-degree3D Display3D MESHES3D displays3D communications360-degree video3DViewers3DSR3D-printing3d3D Range Data Encoding360-degree imaging3D CG Image3D Color Printing3D Reconstruction3D surface structure based halftoning3D COMPRESSION AND ENCRYPTION3D glasses3DGS3D vision3D3D encoding3D IMAGE3A Algorithms3d video3D STIMULI3D DISPLAY3D-high efficiency video coding3D visual representation360 Video3A ALGORITHMS3-D SHAPE RECOVERY360x3D scene capture3d mapping360-Degree Video Technology3D PROFILE3D cinema and TV3D TV3D USER INTERFACES3D range geometry3D localization and mapping3D digitization and dissemination3D Print Appearance3D colour Digital Image Correlation3D Photogrammetry3D RECOVERY3D printer3D INTERACTION360° VIDEO3D imaging3D audio3D ACQUISITION ARCHITECTURE3D projector35MM FILM DIGITIZATION3D mesh simplification3D point cloud3D human-centered technologies3D Scene Reconstruction and Modeling3D-Anisotropic smoothing3DCNN3D-assisted features3D localization3D/4D SCANNING3D Immersion3D Vision3D digital halftoning3D RECONSTRUCTION3D rigid transformations3D modeling3D/2D Visuals3D skeletal joint point cloud; deep learning; PointNet++ method3D depth sensing3D range scanning360° video3ARRI footage3D Curvelet360 IMAGING3D HALFTONING3D shape3D PRINTER3D Communications360-degree content3D printing3D Point Cloud3D affine transformation3D recovery3D Printing3D capture3D Mapping3D scanning3D modelling360 degree images3D Range Data Compression3D Tracking3D EDUCATIONAL MATERIAL3D Video Communications3D/4D DATA PROCESSING AND FILTERING3D Shape Indexing and Retrieval3D scene flow estimation3D connected tube model360-degree videos3D-HEVC3D adaptive halftoning3D Data Sources3D Halftoning3D camera3D Digital Image Correlation3D image compression360-degree Image3D model3D Imaging3D compression3D TRANSFORMATION3D Modeling3D STACK3D surface reproduction3D Range Data3D optical scans3D data processing3D Gaussian Splatting3D surface3D Saliency3D warping3D objects3D scene classification3D video processing360VR3D/4D Data Processing and Filtering3D mapping and localization3D depth-map360-degree video streaming360-video3D MODEL3D PRINTING3D face alignment360-degree images3D Object Detection3D Morphable Model3D stereo vision3D perception360 panorama360 degrees video360-degree art exhibition3D CAMERAS360-degree image projection3D-LUT3D video3D/4D Scanning3D refinement3D display3D-color perception3D mesh3D shape indexing and retrieval3D Telepresence3D image3D Data Processing3D DIGITIZATION METHOD FOR OIL PAINTINGS3DLUT3D-shooting3D position measurement of people3D theater program listing3D Measurement
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.