Mayer et al., 2005 - Google Patents
Segmentation approach and comparison to hyperspectral object detection algorithmsMayer et al., 2005
- Document ID
- 3313481880849143450
- Author
- Mayer R
- Edwards J
- Antoniades J
- Publication year
- Publication venue
- 34th Applied Imagery and Pattern Recognition Workshop (AIPR'05)
External Links
Snippet
This study applies a technique from multi-spectral image classification to object detection in hyperspectral imagery. Reducing the decision surface around the object spectral signature helps extract objects from backgrounds. The object search is achieved through computation …
- 238000001514 detection method 0 title abstract description 25
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/20—Image acquisition
- G06K9/32—Aligning or centering of the image pick-up or image-field
- G06K9/3233—Determination of region of interest
- G06K9/3241—Recognising objects as potential recognition candidates based on visual cues, e.g. shape
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/00624—Recognising scenes, i.e. recognition of a whole field of perception; recognising scene-specific objects
- G06K9/0063—Recognising patterns in remote scenes, e.g. aerial images, vegetation versus urban areas
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/36—Image preprocessing, i.e. processing the image information without deciding about the identity of the image
- G06K9/46—Extraction of features or characteristics of the image
- G06K9/4671—Extracting features based on salient regional features, e.g. Scale Invariant Feature Transform [SIFT] keypoints
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/62—Methods or arrangements for recognition using electronic means
- G06K9/6217—Design or setup of recognition systems and techniques; Extraction of features in feature space; Clustering techniques; Blind source separation
- G06K9/6228—Selecting the most significant subset of features
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/62—Methods or arrangements for recognition using electronic means
- G06K9/6217—Design or setup of recognition systems and techniques; Extraction of features in feature space; Clustering techniques; Blind source separation
- G06K9/6232—Extracting features by transforming the feature space, e.g. multidimensional scaling; Mappings, e.g. subspace methods
- G06K9/6247—Extracting features by transforming the feature space, e.g. multidimensional scaling; Mappings, e.g. subspace methods based on an approximation criterion, e.g. principal component analysis
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/62—Methods or arrangements for recognition using electronic means
- G06K9/6288—Fusion techniques, i.e. combining data from various sources, e.g. sensor fusion
- G06K9/6292—Fusion techniques, i.e. combining data from various sources, e.g. sensor fusion of classification results, e.g. of classification results related to same input data
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/20—Image acquisition
- G06K9/2018—Identifying/ignoring parts by sensing at different wavelengths
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/00624—Recognising scenes, i.e. recognition of a whole field of perception; recognising scene-specific objects
- G06K9/00771—Recognising scenes under surveillance, e.g. with Markovian modelling of scene activity
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/00624—Recognising scenes, i.e. recognition of a whole field of perception; recognising scene-specific objects
- G06K9/00711—Recognising video content, e.g. extracting audiovisual features from movies, extracting representative key-frames, discriminating news vs. sport content
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/00221—Acquiring or recognising human faces, facial parts, facial sketches, facial expressions
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/00006—Acquiring or recognising fingerprints or palmprints
Similar Documents
Publication | Publication Date | Title |
---|---|---|
Du et al. | Random-selection-based anomaly detector for hyperspectral imagery | |
US11067448B2 (en) | Spectral object detection | |
US8189860B2 (en) | Systems and methods of using spatial/spectral/temporal imaging for hidden or buried explosive detection | |
EP2711730A1 (en) | Monitoring of people and objects | |
Pieper et al. | Hyperspectral detection and discrimination using the ACE algorithm | |
US9430842B1 (en) | Material classification fused with spatio-spectral edge detection in spectral imagery | |
Thomas et al. | Applications of grid pattern matching to the detection of buried landmines | |
Ozdil et al. | Representative signature generation for plant detection in hyperspectral images | |
Vongsy et al. | A comparative study of spectral detectors | |
Mayer et al. | Segmentation approach and comparison to hyperspectral object detection algorithms | |
Kwon et al. | Dual-window-based anomaly detection for hyperspectral imagery | |
Kwon et al. | Kernel matched signal detectors for hyperspectral target detection | |
Mayer et al. | A classification approach and comparison to other object identification algorithms for hyperspectral imagery | |
Mayer et al. | Robustness tests for object identification algorithms in hyperspectral imagery | |
Kwon et al. | Kernel RX: a new nonlinear anomaly detector | |
Brown et al. | Nearest neighbor anomaly detector for passively augmented LADAR | |
Mayer et al. | Extending the normalized difference vegetation index (NDVI) to short-wave infrared radiation (SWIR)(1-to 2.5-µm) | |
Uto et al. | Hyperspectral band selection for human detection | |
Ozdil et al. | An Improved Approach for Small Object Detection in Hyperspectral Images | |
Cisz et al. | Performance comparison of hyperspectral target detection algorithms in altitude varying scenes | |
Duman | Methods for target detection in SAR images | |
Duman et al. | Target detection and classification in SAR images using region covariance and co-difference | |
Friesen et al. | Contextual anomaly detection cueing methods for hyperspectral target recognition | |
Thomas et al. | Adaptive spatial sampling schemes for the detection of minefields in hyperspectral imagery | |
Mayer et al. | Extending classification approaches to hyperspectral object detection |