dilatecv

Syntax

R = dilatecv(handle, kernel...)

R = dilatecv(handle, kernel, anchor, iterations, type, color)

Inputs

handle

Handle of an image.

Type: integer

kernel

Structuring element used for dilation. This can be created using the command getstructuringelementcv. An empty matrix, [] can also be used and a default structuring element will be used.

Type: integer | mat

anchor

Optional vector of 2 integers specifying the anchor position. Default value is [-1 -1], indicating the anchor is at the center of the element.

Type: vector

iterations

Optional parameter specifying the number of times dilation is applied. Default value is 1.

Type: integer

type

Optional parameter specifying the pixel extrapolation method. Default value is 0. Valid values are:

0

Type cv::BORDER_CONSTANT - default value

1

Type cv::BORDER_REPLICATE

2

Type cv::BORDER_REFLECT

4

Type cv::BORDER_REFLECT_101

16

Type cv::BORDER_ISOLATED

Type: integer

color

Optional 3-element vector of integers representing blue, green, red (BGR) colors, if type is 0. Black will be the default color if nothing is specified with type.

Type: vector

Outputs

r

Handle of the dilated image.

Type: integer

Examples

handle = imreadcv('image1.jpg');
R = dilatecv(handle, []);

handle = imreadcv('image1.jpg');
kernel = getstructuringelementcv(1, [10 10]);
R = dilatecv(handle, kernel, [-1 -1], 1, 0, [255 0 0]);

Detect the edges and dilate the output:

imgoriginal = imreadcv('Dog.jpg',1);
figure(1);
imshowcv(imgoriginal);

%Conver the image to gray scale
img = cvtcolorcv(imgoriginal, 6);

edges = cannycv(img, 70, 180);
dilatededges = dilatecv(edges, []);

figure(2);
imshowcv(erodededges);