Keywords l

LADAR Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
Section: Laser Sensors for Range, Time of Flight (H3)
Section: LIDAR, LADAR -- Range data (H2)
Section: Remote Sensing, Cartography, Aerial Images, Buildings, Roads, Terrain, ATR (H)
* Model-Based Automatic Target Recognition (ATR) System for Forward-Looking Groundbased and Airborne Imaging Laser Radars (Lada

LAI Section: LAI, Leaf Area Index, Land Cover Analysis (H3)
Section: Remote Sensing, Cartography, Aerial Images, Buildings, Roads, Terrain, ATR (H)

Land Cover Section: Global-Scale Analysis, Global Land Cover Analysis (H3)
Section: Land Cover Analysis, Specific Location Applications, Site Analysis, Site Specific (H3)
Section: Land Cover Analysis, Water Detection, Water Areas (H3)
Section: Land Cover, Land Use, General Problems, Remote Sensing (H3)
Section: Remote Sensing, Cartography, Aerial Images, Buildings, Roads, Terrain, ATR (H)

Land Mines Section: Ground Penetrating Radar, Buried Objects, UXO, Landmines (H3)
Section: Remote Sensing, Cartography, Aerial Images, Buildings, Roads, Terrain, ATR (H)
* Polarimetric processing of coherent random noise radar data for buried object detection
* Ultrawideband Radar Images of the Surface Disturbance Produced by a Submerged, Mine-Like Object

Landmarks Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Section: Localization, Georeference, Urban Regions, City Models, Building Models (H4)
Section: Navigation, Landmarks (H3)
Section: Qualitative Navigation, Drop Off, Where in the World or Region (H4)
* Visual Navigation for a Mobile Robot Using Landmarks

LandSat Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Section: Radiometric Calibration of LandSat Scanners, Images (H3)

Landsat, History Section: Remote Sensing, Cartography, Aerial Images, Buildings, Roads, Terrain, ATR (H)
* Landsat Program: Recent History and Prospects, The

Landslide Section: Landslide Analysis, Damage Assessment, Deformations (H4)
Section: Remote Sensing, Cartography, Aerial Images, Buildings, Roads, Terrain, ATR (H)

Lane Departure Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Section: Lane Departure Detection, Lane Control Assistance, Lateral Control (H4)

Lane Detection Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Section: Lane Departure Detection, Lane Control Assistance, Lateral Control (H4)
Section: Lane Detection, Lane Following, White Line Detection (H3)

Lane Following Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Section: Lane Departure Detection, Lane Control Assistance, Lateral Control (H4)
Section: Lane Detection, Lane Following, White Line Detection (H3)

Language Analysis Section: Grammar Based Analysis, Language Issues (H3)
Section: New Unsorted Entries, and Other Miscellaneous Papers (H)

Language Recognition Section: Language Recognition, Multi-Language Documents (H3)
Section: OCR, Document Analysis and Character Recognition Systems (H)

Laparoscopy Section: Laparoscopy, Surgery (H2)
Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)

Large Scale Database Section: Image Databases, Large Scale Systems, Web-Scale System (H3)
Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)

Laser Range Finders Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
Section: Laser Sensors for Range, Time of Flight (H3)

Laser Scanners Section: Buildings from Depth Data, LiDAR Data (H2)
Section: Remote Sensing, Cartography, Aerial Images, Buildings, Roads, Terrain, ATR (H)

Laser Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
Section: 3-D Shape from X -- Shading, Textures, Lasers, Structured Light, Focus, Line Drawings (H)
Section: Calibration -- Lidar, Laser Scanner, Depth Sensor, Scanner Error Analysis (H3)
Section: Shape from Laser Ranging and Structured Light Images (H1)

Layout Analysis Section: Document Layout, Document Segmentation, Page Layout, Structure Analysis (H3)
Section: OCR, Document Analysis and Character Recognition Systems (H)

LBP Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
Section: Face Analysis, Local Binary Patters for Face Recognition (H3)
Section: Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)
Section: Local Binary Patterns, LBP, Point Features (H3)
Section: Local Binary Patterns, LPB for Texture (H3)

LDA Definition:* Linear Discriminant Analysis.
Section: Discriminant Analysis (H3)
Section: Invariants -- Linear Discriminant Analysis, Fisher Linear Discriminant (H3)
Section: LDA in Face Recognition (H4)
Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)

Leaf Area Index Section: LAI, Leaf Area Index, Land Cover Analysis (H3)
Section: Remote Sensing, Cartography, Aerial Images, Buildings, Roads, Terrain, ATR (H)

Leaf Shape Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
Section: Plants, Leaf Shapes, Leaf Analysis, Leaf Segmentation (H4)

Learning Models Section: Learning Model Descriptions (H3)
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)

Learning Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
Section: Evaluation and Analysis of Learning Techniques (H2)
Section: Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)
Section: Imbalanced Sample Sizes, Imbalanced Data (H3)
Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
Section: Learning -- Conference Listing (H2)
Section: Learning Face Detection, Neural Nets, SVM (H3)
Section: Learning for Human Action Recognition and Detection (H4)
Section: Learning for Principal Components, Eigen Representations (H3)
Section: Learning in Computer Vision (H1)
Section: Learning Object Descriptions, Object Recognition (H2)
Section: Learning, General Non-Vision Learning Issues (H2)
Section: Learning, General Surveys, Overviews (H2)
Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
Section: Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities (H)
Section: Multiple Instance Learning (H2)
Section: OCR, Document Analysis and Character Recognition Systems (H)
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
* Face Recognition with Learning Machines
* Hidden Tree Markov Models for Document Image Classification
* Learning Structural Descriptions from Examples
* Learning Texture-Discrimination Masks
* Optimizing Learning in Image Retrieval
* RIEVL: Recursive Induction Learning in Hand Gesture Recognition
* Some Experiments in Applying Inductive Inference Principles to Surface Reconstruction
26 for Learning

Least Median Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
* Least Median of Squares Based Robust Analysis of Image Structure

Least Squares Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
Section: Least Squares Applied to Restoration (H2)
* Sequential Coordinate-Wise Algorithm for the Non-negative Least Squares Problem

Left Luggage Section: Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities (H)
Section: Unattended Package, Abandoned Luggage, Left Luggage (H4)

Left Ventricle Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
Section: Deformable Models, Cardiac Motion Models for Volumes, Left Ventricle (H3)

Lens Distortion Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Section: Camera Calibration, Lens Distortion, Aberration, Radial Distortion, Internal Parameters (H2)
* Calibration of Stereo Cameras Using a Non-Linear Distortion Model
* Efficient and Accurate Camera Calibration Technique for 3-D Machine Vision, An

Leukocyte Section: Blood Cells, Counting, Extraction, Analysis (H2)
Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)

Level Set Methods Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
Section: Optical Flow Field Computations and Use (H)
* Image-Processing: Flows under Min/Max Curvature and Mean-Curvature
* Level Set Methods: Evolving Interfaces in Geometry, Fluid Mechanics, Computer Vision and Materials Science

Level Set Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
Section: Level Set Models for Volumes (H3)
Section: Level Set Segmentation, Level Set Methods (H2)
Section: Level Sets, Medical Image Segmentation (H3)
Section: Level Sets, Shape Models, Prior Shape Models (H3)
Section: Motion Analysis -- Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
* new time dependent model based on level set motion for nonlinear deblurring and noise removal, A
8 for Level Set

Libraries Section: Document Retrieval Systems, Databases and Issues, Libraries (H2)
Section: OCR, Document Analysis and Character Recognition Systems (H)

License Plate Recognition Section: License Plate Recognition, Extraction, Analysis (H3)
Section: Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities (H)
* Large-scale privacy protection in Google Street View

License Plates Section: License Plate Recognition, Extraction, Analysis (H3)
Section: Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities (H)

LIDAR Calibration Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
Section: Calibration -- Laser Scanner Multi-Path, Multipath (H3)
Section: Calibration -- Lidar, Laser Scanner, Depth Sensor, Scanner Error Analysis (H3)
Section: Laser Scanner Calibration -- Calgary Group, Lichti (H3)

LiDAR Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Section: Buildings from Depth Data, LiDAR Data (H2)
Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
Section: DEM, DSM, DTM, Generation Using Radar, SAR, IFSAR (H2)
Section: Forest Analysis, Canopy Heights, LiDAR (H4)
Section: Forest Analysis, Depth, LiDAR, Laser Scanner, IFSAR (H4)
Section: Fusion, Range or Depth and Intensity or Color Data (H3)
Section: Laser Sensors for Range, Time of Flight (H3)
Section: Lidar for Land Cover, Laser Scanners for Land Cover, Remote Sensing (H3)
Section: Radiometric Calibration of Laser Scanners, LIDAR (H3)
Section: Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
Section: Remote Sensing, Cartography, Aerial Images, Buildings, Roads, Terrain, ATR (H)
12 for LiDAR

Lidar, Roads Section: Remote Sensing, Cartography, Aerial Images, Buildings, Roads, Terrain, ATR (H)
Section: Road Extraction in Radar, SAR, Lidar, Laser, Depth (H2)

Lie Groups Section: Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
* Dominant-Subspace Invariants

Lifelog Section: Lifelog (H4)
Section: Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities (H)

Lifting Operator Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
Section: Wavelet Lifting Operator, Transform (H4)

Light Field Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
Section: Light Field Cameras and Analysis (H2)

Light Source Direction Section: 3-D Shape from X -- Shading, Textures, Lasers, Structured Light, Focus, Line Drawings (H)
Section: Light Source Detection, Light Source Estimation (H2)
Section: Light Source Direction Computations, Illumination Information, Illuminant (H3)
* Estimation of Illuminant Direction, Albedo, and Shape from Shading

Lightfield Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
Section: Light Field Cameras and Analysis (H2)

Lighting Model Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
Section: Lighting Effects, View Generation, Graphics Issues (H3)

Lightness Section: Color Constancy, Retinex (H2)
Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)

Line Adjacency Graph Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
Section: Run-Length Coding Representations and Operations (H2)

Line Approximation Section: Edge Detection and Analysis, Lines, Segments, Curves, Corners, Hough Transform (H)
Section: Generation of Straight Line Segments or Curve Partitions (H1)

Line Detection Section: Edge Detection and Analysis, Lines, Segments, Curves, Corners, Hough Transform (H)
Section: Hueckel -- Basis Functions, Model Fitting for Edge Detection (H2)
Section: Line Detectors, Direct Detection of Straight Lines (H2)
Section: Remote Sensing, Cartography, Aerial Images, Buildings, Roads, Terrain, ATR (H)
Section: Road Following, Road Tracking Systems, Connecting Fragments, Extracting Fragments (H2)
Section: Road Network Detection, Road Extraction Systems (H1)
* Mathematical Models for Automatic Line Detection
7 for Line Detection

Line Drawings Section: 3-D Shape from X -- Shading, Textures, Lasers, Structured Light, Focus, Line Drawings (H)
Section: Shape from Line Drawings, Junction Labeling (H1)
Section: Surface and Shape from Contours or Silhouettes (H1)
* Extraction of the Line Drawing of 3-Dimensional Objects by Sequential Illumination from Several Directions

Line Drawings, Analysis Section: 3-D Shape from X -- Shading, Textures, Lasers, Structured Light, Focus, Line Drawings (H)
Section: Line Drawing Analysis (H2)

Line Drawings, Shape Section: 3-D Shape from X -- Shading, Textures, Lasers, Structured Light, Focus, Line Drawings (H)
Section: Shape from Line Drawing (H2)

Line Following Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Section: Lane Detection, Lane Following, White Line Detection (H3)

Line Labeling Section: 3-D Shape from X -- Shading, Textures, Lasers, Structured Light, Focus, Line Drawings (H)
Section: Line Labeling Techniques (H2)
Section: Shape from Line Drawings, Junction Labeling (H1)

Line Labels Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
* Extracting a Valid Boundary Representation from a Segmented Range Image

Line Matching Section: 2-D Lines with 2-D Structure (H2)
Section: 2-D Lines with 3-D Structure (H2)
Section: 3-D Lines with 3-D Structure (H2)
Section: Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)

Line of Sight Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Section: Visibility Analysis, Sight Lines, Line of Sight (H3)

Line Segments Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
Section: Edge Detection and Analysis, Lines, Segments, Curves, Corners, Hough Transform (H)
Section: Generation of Straight Line Segments or Curve Partitions (H1)
Section: Line Detectors, Direct Detection of Straight Lines (H2)
* Bayesian Method for Fitting Parametric and Nonparametric Models to Noisy Data, A

Line Vectorization Section: Edge Detection and Analysis, Lines, Segments, Curves, Corners, Hough Transform (H)
Section: Line Vectorization, Document Analysis (H2)

Linear Constraints Section: Optical Flow Field Computations and Use (H)
* Performance of Camera Translation Direction Estimators from Optical-flow: Analysis, Comparison, and Theoretical Limits, The

Linear Discriminant Analysis Section: Discriminant Analysis (H3)
Section: Invariants -- Linear Discriminant Analysis, Fisher Linear Discriminant (H3)
Section: LDA in Face Recognition (H4)
Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)

Linear Features Section: Edge Detection and Analysis, Lines, Segments, Curves, Corners, Hough Transform (H)
Section: Extended Linear Features - Beyond Segments (H2)
Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
Section: Line Vectorization, Document Analysis (H2)
* Approach to the Recognition of Contours and Line-Shaped Objects, An

Linear Prediction Section: Linear Prediction Techniques (H3)
Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)

Linear Programming Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
* Linear Programming Approach fo the Weighted Graph Matching Problem, A

Lines Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
Section: Digital Geometry -- Lines, Curves and Contours (H3)

Lines, Colinear Section: Colinear Line Segments (Collinear) (H
Section: Edge Detection and Analysis, Lines, Segments, Curves, Corners, Hough Transform (H)

Lines, General Section: Edge Detection and Analysis, Lines, Segments, Curves, Corners, Hough Transform (H)
Section: General Systems for Lines and Curves (H2)

Linkoping Univ. * *Linkoping University

Lip Detection Section: Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)
Section: Mouth Location, Lip Location, Detection (H3)

Lip Reading Section: Combined Audio Visual Recognition and Analysis (H3)
Section: Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)
Section: Lipreading, Lip Reading, Lip Tracking (H2)

Lipreading Section: Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)
Section: Lipreading, Lip Reading, Lip Tracking (H2)

Liveness Section: Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)
Section: Liveness Detection, Spoofing, Faces, Other Biometrics (H3)
Section: Liveness Detection, Spoofing, Fingerprint Recognition (H3)

Liver Disease Section: Liver Disease, Tomography, CAT Analysis (H3)
Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)

Local Binary Patterns Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
Section: Face Analysis, Local Binary Patters for Face Recognition (H3)
Section: Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)
Section: Local Binary Patterns, LBP, Point Features (H3)

Localization Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Section: Localization, Georeference, Urban Regions, City Models, Building Models (H4)
Section: Localization, GPS Assisted, GNSS Assisted, Guidance System Assisted, Other Annotation (H4)
Section: Localization, Where is the robot, Where is the camera (H3)
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
* more you learn, the less you store: Memory-controlled incremental SVM for visual place recognition, The

Log-Polar Sensor Section: Optical Flow Field Computations and Use (H)
* On the Estimation of Depth from Motion Using an Anthropomorphic Visual Sensor

Log-Polar Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Section: Complex Log Mapping, Algorithms and Sensors (H2)
Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
Section: Optical Flow Field Computations and Use (H)
* Binocular Fusion Revisited Utilizing a Log-Polar Tessellation
* Direct Computation of the Focus of Expansion from Velocity Field Measurements
* Disparity Estimation on Log-Polar Images and Vergence Control
7 for Log-Polar

Log Mapping Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
Section: Complex Log Mapping, Algorithms and Sensors (H2)
Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
Section: Motion Analysis -- Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
Section: Optical Flow Field Computations and Use (H)
* Complex Logarithmic Mapping and the Focus of Expansion
* Direct Computation of the Focus of Expansion
* Direct Estimation of Time-to-Impact from Optical Flow
* Geometric invariance in space-variant vision systems: The exponential chirp transform
* Motion Stereo Using Ego-Motion Complex Logarithmic Mapping
* On the Advantage of Polar and Log-Polar Mapping for Direct Estimation of Time-to-Impact from Optical Flow
* Position, Rotation and Scale Invarient Optical Correlation
12 for Log Mapping

Log Polar Mapping Section: Motion Analysis -- Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
* Segmentation of Frame Sequence Obtained by a Moving Observer

Logo Recognition Section: Analysis of Graphics, Symbols, Trademarks, Logos, Icons (H3)
Section: OCR, Document Analysis and Character Recognition Systems (H)
Section: Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
* Analysis of Compressed Document Images for Dominant Skew, Multiple Skew, and Logotype Detection
* Applying Algebraic and Differential Invariants for Logo Recognition
* Content-Based Retrieval for Trademark Registration
* Content-Based Trademark Retrieval System Using Visually Salient Features
* Neural Based Architecture for Spot-Noisy Logo Recognition, A
* Retrieval of Images from Image Databases: Trademarks, The
* Shape-Based Retrieval: A Case-Study with Trademark Image Databases
* Trademark Shape-Recognition Using Closed Contours
* Trademark Shapes Description by String-Matching Techniques
* Using Negative Shape Features for Logo Similarity Matching
13 for Logo Recognition

Logs Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
Section: Inspection -- Lumber, Logs, Wood (H3)

Lossless Compression Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
Section: Lossless Coding, Lossless Compression, Transmission (H2)
* Lossless Compression of AVIRIS Images by Vector Quantization, The

Low Bit Rate Coding Section: Computing Very Low Bitrate, 3-D and Object Based Coding (H4)
Section: High Rate Compression, Low Bit Rate Compression, Region Based Coding (H2)
Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
Section: Motion Compensation, Block, Region, Object, and Low Bit Rate Coding (H2)
Section: Motion Compensation, Low Bit Rate, Survey, Evaluations (H4)
Section: Very Low Bitrate, 3-D and Object Based Coding (H4)

LSB Section: Data Hiding, Steganography, LSB, Least Significant Bit (H3)
Section: OCR, Document Analysis and Character Recognition Systems (H)

Lumber Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
Section: Inspection -- Lumber, Logs, Wood (H3)

Lung Cancer Section: Lungs, and Lung Cancer Image Analysis (H2)
Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)

Lung Nodules Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)
Section: Pulmonary Nodules, Lung Nodules (H3)

Lungs Section: Airway Tree Structure (H3)
Section: Bronchoscopy Systems, Bronchial Analysis (H3)
Section: Lungs, and Lung Cancer Image Analysis (H2)
Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)
Section: Pulmonary Nodules, Lung Nodules (H3)
Section: Thorax, Thoracic Analysis (H3)

Lymph Nodes Section: Medical Applications -- Lymph Nodes (H2)
Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)

Lymphoma Section: Blood Cell Cancers, Lymphoma, Leukemia (H3)
Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)

Index for "m"


Last update:11-Nov-17 13:53:35
Use price@usc.edu for comments.