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Blob Detector
The
Blob Detector node in AugeLab Studio is used to detect blobs or regions of interest in an input image based on specified parameters.The
Blob Detector node applies blob detection algorithms to an input image, searching for regions that match certain characteristics such as size, shape, and intensity. The node outputs the input image with detected blobs highlighted, along with additional information about the detected blobs.- Node Title: Blob Detector
- Node ID: OP_NODE_BLOB_DETECTOR
The
Blob Detector node has the following input socket:- 1.Image: The input image on which blob detection will be performed.
The
Blob Detector node has the following output sockets:- 1.Detected Blobs Image: The input image with detected blobs highlighted.
- 2.Number of Blobs: The total number of blobs detected in the image.
- 3.Blob Positions: The positions of the detected blobs as (x, y) coordinates.
- 4.Blob Sizes: The sizes of the detected blobs.
The
Blob Detector node provides the following adjustable parameters to control the blob detection:- Threshold Range: Specifies the range of pixel intensity values used to determine the threshold for blob detection. Blobs with intensities outside this range will be ignored.
- Area Range: Specifies the range of blob areas (in pixels) to consider during detection. Blobs with areas outside this range will be ignored.
- Circularity Range: Specifies the range of circularity values to consider during detection. Circularity is a measure of how close a blob's shape is to a circle. Blobs with circularity values outside this range will be ignored.
- Convexity Range: Specifies the range of convexity values to consider during detection. Convexity is a measure of how convex a blob's shape is. Blobs with convexity values outside this range will be ignored.
- Inertia Range: Specifies the range of inertia values to consider during detection. Inertia is a measure of how elongated a blob's shape is. Blobs with inertia values outside this range will be ignored.
- 1.Drag and drop the
Blob Detectornode from the node library onto the canvas in AugeLab Studio. - 2.Connect the input image to the Image input socket of the
Blob Detectornode. - 3.Adjust the parameter sliders to set the desired blob detection thresholds and ranges.
- 4.Run the pipeline.
- 5.The
Blob Detectornode will detect blobs in the input image based on the specified parameters. - 6.The output image will show the input image with detected blobs highlighted.
- 7.The number of detected blobs, their positions, and sizes will be provided through the respective output sockets.
- 8.Use the output information for further processing, analysis, or visualization.
- The
Blob Detectornode uses thecv2.SimpleBlobDetectorclass from the OpenCV library to perform blob detection. - The
SimpleBlobDetectorclass provides various parameters to control the detection process, such as thresholding, area filtering, circularity filtering, convexity filtering, and inertia filtering. - The node allows you to adjust these parameters using sliders to fine-tune the blob detection based on your specific requirements.
- The output image will show the detected blobs as circular markers overlaid on the input image.
- The number of detected blobs, their positions, and sizes can be useful for further analysis or processing tasks.
- The
Blob Detectornode is commonly used in computer vision applications for object recognition, feature extraction, image segmentation, and tracking.
That concludes the documentation for the
Blob Detector node in AugeLab Studio. This node allows you to detect blobs or regions of interest in an input image based on specified parameters. Use this node for object recognition, feature extraction, and various computer vision tasks involving blob detection.