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Corner Detector
The
Corner Detector node in AugeLab Studio is used to detect corner patterns on an input image. It applies corner detection algorithms such as Harris Corner or Shi-Tomasi Corner to identify and mark corners in the image.The
Corner Detector node utilizes corner detection algorithms to identify corners in an image. It outputs an image with the detected corners marked, as well as the total number of corners found.- Node Title: Corner Detector
- Node ID: OP_NODE_CORNER
The
Corner Detector node has the following input socket:- 1.Input Image: The input image to be analyzed for corner detection.
The
Corner Detector node has the following output sockets:- 1.Detected Corners: An image with the detected corners marked.
- 2.Number of Corners: The total number of corners detected in the image.
The
Corner Detector node provides the following adjustable parameters:- Detector Type: The type of corner detector algorithm to use. It can be either Harris Corner or Shi-Tomasi Corner.
- Threshold: The threshold value for corner detection. Lower values may result in more corners being detected, while higher values may lead to fewer detections.
- 1.Drag and drop the
Corner Detectornode from the node library onto the canvas in AugeLab Studio. - 2.Connect the input image to the Input Image input socket of the
Corner Detectornode. - 3.Choose the desired corner detection algorithm (Harris Corner or Shi-Tomasi Corner) using the Detector Type drop-down menu.
- 4.Adjust the Threshold slider to set the desired threshold value for corner detection.
- 5.Run the pipeline.
- 6.The
Corner Detectornode will apply the selected corner detection algorithm to the input image. - 7.Detected corners will be marked on the output image.
- 8.The Detected Corners output will provide the image with the detected corners marked.
- 9.The Number of Corners output will indicate the total number of corners detected in the image.
- 10.Adjust the Detector Type and Threshold parameters to fine-tune the corner detection based on the input image and desired sensitivity.
- 11.Use the output image and the number of corners for further analysis, visualization, or downstream processing.
- The
Corner Detectornode utilizes corner detection algorithms to identify and mark corners in an input image. - It applies either the Harris Corner or Shi-Tomasi Corner algorithm based on the selected detector type.
- Detected corners are marked on the output image for visualization purposes.
- The Number of Corners output indicates the total number of corners detected in the image.
- Adjusting the Threshold parameter controls the sensitivity of corner detection. Lower values result in more corners being detected, while higher values lead to fewer detections.
- The
Corner Detectornode is useful in various applications such as feature extraction, image registration, object tracking, and image stitching, where identifying and analyzing corner patterns is necessary.
That concludes the documentation for the
Corner Detector node in AugeLab Studio. This node enables you to detect corner patterns in an input image using corner detection algorithms such as Harris Corner or Shi-Tomasi Corner. Use this node to identify and analyze corners in various computer vision applications, feature extraction, object tracking, or image stitching processes.