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TextureFeatures

The component uses VLFeat library to extract SIFT/MSER keypoints and SIFT descriptors from grayscale images. The descriptors are used in texture analysis. In order to use this component, you have to get VLFEat (>=0.99) and extract it under the bundle folder so, that the vl_setup.m file will be in location: [BUNDLE_HOME]/lib/vlfeat/toolbox/vl_setup.m.

The "sift" method searches for keypoints with given parameters and produces the descriptors for those. The "dsift" or dense sift method extracts descriptors over a grid of keypoints. The "mser" method classifies the pixels and produces a segmented image and keypoint locations.

Version 1.0
Bundle anima
Categories Image Analysis
Authors Ville Rantanen (ville.rantanen@helsinki.fi)
Issue tracker View/Report issues
Requires Matlab ; VLFeat ; download (bash)
Source files component.xml imagevlfeat.m pixelframe.m execute.m
Usage Example with default values

Inputs

Name Type Mandatory Description
in ImageList Mandatory Source grayscale images
names ImageList Optional Source images for naming of the data

Outputs

Name Type Description
images ImageList Result images, or depending on the method, visualizations.
out CSVList Result features and keypoints, separate CSV file for each input image file.

Parameters

Name Type Default Description
dsiftStep float 1 Extracts a SIFT descriptor each STEP pixels. Method: dsift
method string "sift" Method to use sift,dsift or mser
mserBrightOnDark boolean true Detect bright-on-dark MSERs. This corresponds to MSERs of the inverted image. Method: mser
mserDarkOnBright boolean true Detect dark-on-bright MSERs. This corresponds to MSERs of the original image. Method: mser
mserDelta float 5 DELTA parameter of the MSER algorithm. Roughly speaking, the stability of a region is the relative variation of the region area when the intensity is changed of +/- Delta/2 (in UINT8). Method: mser
mserDraw string "regions" Choices: regions, ellipses. Output image has the regions with overlaps, or the fitted ellipses on the regions. Method: mser
mserMaxArea float 0.75 Set the maximum area of the regions relative to the image domain area. Method: mser
mserMaxVariation float 0.25 Set the maximum variation (absolute stability score) of the regions. Method: mser
mserMinArea float 0 Set the minimum area of the regions relative to the image domain area. Method: mser
mserMinDiversity float 0.2 Set the minimum diversity of the region. When the relative area variation of two nested regions is below this threshold, then only the most stable one is selected. Method: mser
siftEdgeThresh float 10 Non-edge selection threshold. Method: sift
siftFirstOctave float 0 Index of the first octave of the DoG scale space. Method: sift
siftLevels float 3 Number of levels per octave of the DoG scale space. Method: sift
siftMagnif float 3 Descriptor magnification factor. The scale of the keypoint is multiplied by this factor to obtain the width (in pixels) of the spatial bins. Method: sift,dsift
siftOctaves float 0 Number of octaves of the DoG scale space, defaults to "max possible". Method: sift
siftPeakThresh float 0 Peak selection threshold. Method: sift
siftSize float 2 The variance of the Gaussian window that determines the descriptor support. It is expressend in units of spatial bins. Method: sift,dsift

Test cases

Test case Parameters IN
in
IN
names
OUT
images
OUT
out
case1_sift properties in (missing) images out

metadata.timeout=60

case2_mser properties in (missing) images out

method=mser,
mserDelta=15,
mserMaxArea=0.4,
mserMinArea=0.04,
mserDraw=regions


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