edge_detection

Detects the edges with the Sobel, Laplacian or Canny (cv::Canny()) edge detector.

opencv_apps	1.11 and later (ROS 1), 3.0.0 and later (ROS 2)
ROS	noetic, ROS One, jazzy, kilted, lyrical and later
OpenCV	any version of the distributions
Group	Image filters, the nodes of which publish the processed image in ~/image

Usage

# ROS 2
ros2 launch opencv_apps edge_detection.launch.xml image:=/camera/image_raw debug_view:=false
# ROS 1
roslaunch opencv_apps edge_detection.launch image:=/camera/image_raw debug_view:=false

Try it with the demo video

Download the input video of the demo above, publish it as image with image_publisher, and run the node on it, in the terminals:

wget https://ros-perception.github.io/opencv_apps/media/clips/street.mp4
# terminal 1: publish the video as image in a loop
ros2 run image_publisher image_publisher_node street.mp4 --ros-args -p publish_rate:=10.0 -r image_raw:=image
# terminal 2: run the node with the parameters of the demo
ros2 launch opencv_apps edge_detection.launch.xml image:=image edge_type:=2 node_name:=edge_canny_detection
# terminal 3: view the result
ros2 run rqt_image_view rqt_image_view /edge_canny_detection/image

Canny.

In ROS 1:

# terminal 1
rosrun image_publisher image_publisher street.mp4 _publish_rate:=10 __name:=camera
# terminal 2
roslaunch opencv_apps edge_detection.launch image:=camera/image_raw edge_type:=2 node_name:=edge_canny_detection

See Credits of the demo videos for the license of the video.

Subscribed topics

Topic	Type
image	sensor_msgs/msg/Image

Published topics

Topic	Type
~/image	sensor_msgs/msg/Image

Parameters

See also the common parameters.

Name	Type	Default (range)	Changed at run time	Description
L2gradient	bool	false	yes	Flag, indicating whether a more accurate L_2 norm should be used to calculate the image gradient magnitude ( L2gradient=true ), or whether the default L_1 norm is enough ( L2gradient=false ).
apertureSize	int	3 (1 - 10)	yes	Aperture size for the Sobel() operator.
apply_blur_post	bool	false	yes	Flag, applying GaussianBlur() to output(edge) image
apply_blur_pre	bool	true	yes	Flag, applying Blur() to input image
canny_threshold1	int	100 (0 - 500)	yes	First threshold for the hysteresis procedure.
canny_threshold2	int	200 (0 - 500)	yes	Second threshold for the hysteresis procedure.
edge_type	int	0 (0 - 2)	yes	Edge Detection Methods, 0: Sobel, 1: Laplace, 2: Canny
postBlurSigma	double	3.2 (0 - 10)	yes	Sigma for the GaussianBlur() operator.
postBlurSize	int	13 (3 - 31)	yes	Aperture size for the Blur() operator.
queue_size	int	3	no, restart the node	Specigy queue_size of input image subscribers

Source

src/nodelet/edge_detection_nodelet.cpp, launch/edge_detection.launch.xml