Representation
Feature Selection
| feateval | Evaluation of a feature set | |
| featrank | Ranking of individual feature permormances | |
| featsel | Feature Selection | |
| featselb | Backward feature selection | |
| featself | Forward feature selection | |
| featsellr | Plus-l-takeaway-r feature selection | |
| featseli | Feature selection on individual performance | |
| featselo | Branch and bound feature selection | |
| featselp | Floating forward feature selection | |
| featselv | Selection of varying features |
Mappings
| bhatm | Two-class Bhattacharryya mapping | |
| cmapm | Compute some special maps | |
| fisherm | Fisher mapping | |
| chernoffm | Chernoff mapping | |
| invsigm | Inverse sigmoid map | |
| filtm | Arbitrary operation on objects in datafiles/datasets | |
| gaussm | Mixture of Gaussians density estimation | |
| kernelm | Kernel mapping | |
| klm | Decorrelation and Karhunen Loeve mapping (PCA) | |
| klms | Scaled version of klm, useful for prewhitening | |
| knnm | k-Nearest neighbor density estimation | |
| nlfisherm | Nonlinear Fisher mapping | |
| normm | Object normalization map | |
| parzenm | Parzen density estimation | |
| parzenml | Optimization of smoothing parameter in Parzen density estimation. | |
| pca | Principal Component Analysis | |
| proxm | Proximity mapping and kernel construction | |
| reducm | Reduce to minimal space mapping | |
| remoutl | Remove outliers | |
| scalem | Compute scaling data | |
| sigm | Simoid mapping | |
| spatm | Augment image dataset with spatial label information | |
| userkernel | User supplied kernel definition | |
| gtm | Fit a Generative Topographic Mapping (GTM) by EM | |
| plotgtm | Plot a Generative Topographic Mapping in 2D | |
| som | Simple routine computing a Self-Organizing Map (SOM) | |
| plotsom | Plot a Self-Organizing Map in 2D |
Handling images in datasets and datafiles
| data2im | Convert dataset to image | |
| getobjsize | Retrieve image size of feature images in datasets | |
| getfeatsize | Retrieve image size of object images in datasets | |
| obj2feat | Transform object images to feature images in dataset | |
| feat2obj | Transform feature images to object images in dataset | |
| im2feat | Convert image to feature in dataset | |
| im2obj | Convert image to object in dataset | |
| imsize | Retrieve size of specific image in datafile | |
| im_patch | Find / generate patches in object images | |
| band2obj | Convert image bands to objects in dataset | |
| bandsel | Select image bands in dataset or datafile | |
| selectim | Select image in multi-band object image dataset/datafile | |
| show | Display objects in datasets, datafiles and mappings |
Operations on images in datasets and datafiles
| classim | Classify image using a given classifier | |
| dataim | Image operation on dataset images (features or objects) | |
| doublem | Convert datafile images into double | |
| filtim | Image operation on objects in datafiles/datasets | |
| datgauss | Filter dataset image by Gaussian filter | |
| datunif | Filter dataset image by uniform filter | |
| spatm | Augment image dataset with spatial label information | |
| im_box | Bounding box | |
| im_fft | FFT transform (and more) | |
| im_gray | Multi-band to gray-value conversion | |
| im_label | Labeling binary images | |
| im_maxf | Maximum filter | |
| im_minf | Minimum filter | |
| im_norm | Normalize images w.r.t. mean and variance | |
| im_resize | Resize images | |
| im_rotate | Rotate images | |
| im_scale | Scale images | |
| im_select_blob | Select largest blob | |
| im_skel_meas | Skeleton measurements | |
| im_threshold | Threshold images |
Feature extraction from images in datasets and datafiles
| histm | Convert images to histograms | |
| im_harris | Find Harris points in images | |
| im_moments | Computes moments as features from object images | |
| im_mean | Computes center of gravity | |
| im_measure | Computes some measurements | |
| im_profile | Computes image profiles | |
| im_stat | Compute some simple statistics |
