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IPCV - Image Processing and Computer Vision Toolbox for Scilab >> Feature Detection, Description and Matching > imdetect_MSER

imdetect_MSER

Detect features from an image with MSER algorithm

Syntax

fobj = imdetect_MSER(im [,delta [,min_area [,max_area [,max_variation [,min_diversity [,max_evolution [,area_threshold [,min_margin [,edge_blur_size]]]]]]]]]);

Parameters

im :

Input image

delta:

Compares (sizei - sizei-delta)/sizei-delta. Default value is 5.

min_area :

Prune the area which smaller than minArea. Default value is 60.

max_area :

Prune the area which bigger than maxArea. Default value is 14400.

max_variation :

Prune the area have simliar size to its children. Default value is 0.25.

min_diversity :

For color image, trace back to cut off mser with diversity less than min_diversity. Default value is 0.2.

max_evolution :

For color image, the evolution steps. Default value is 200.

area_threshold :

For color image, the area threshold to cause re-initialize. Default value is 1.01.

min_margin :

For color image, ignore too small margin. Default value is 0.003.

edge_blur_size :

For color image, the aperture size for edge blur. Default value is 5.

fobj :

Features object contains following fields -

type :

Type of features

n :

Numbers of detected features

x :

Coordinates of the detected features - X

y :

Coordinates of the detected features - Y

size :

Size of detected features

angle :

keypoint orientation

response :

The response by which the most strong keypoints have been selected.

octave :

pyramid octave in which the keypoint has been detected

class_id :

object id

Description

This function used to detect the features of an image using MSER method

Examples

S = imcreatechecker(8,8,[1 0.5]);
fobj = imdetect_MSER(S,1);
imshow(S); plotfeature(fobj);

See also

Authors

Bibliography

1. OpenCV 2.4 Online Documentation


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