Representation – Image Operations
| classim | Classify image using a given classifier | more routines |
| 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 |
elements:
datasets
datafiles
cells and doubles
mappings
classifiers
mapping types.
operations:
datasets
datafiles
cells and doubles
mappings
classifiers
stacked
parallel
sequential
dyadic.
user commands:
datasets
representation
classifiers
evaluation
clustering
examples
support routines.
introductory examples:
Introduction
Scatterplots
Datasets
Datafiles
Mappings
Classifiers
Evaluation
Learning curves
Feature curves
Dimension reduction
Combining classifiers
Dissimilarities.
advanced examples.
