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Image Threshold
The
Image Threshold node in AugeLab Studio is used to apply thresholding to an input image, converting it into a binary image based on a specified threshold value.The
Image Threshold node applies thresholding to the input image, resulting in a binary image where pixels are classified into two categories based on the threshold value: foreground and background.- Node Title: Image Threshold
- Node ID: OP_NODE_THRESHOLD
The
Image Threshold node has the following input socket:- ImageAny: The input image to be thresholded. Connect an image to this socket.
The
Image Threshold node has the following output socket:- ImageGray: The thresholded binary image.
The
Image Threshold node allows you to configure the following properties:- Threshold Type: Select the type of thresholding to be applied. The available options are:
- THRESH_BINARY: Binary thresholding. Pixels with values above the threshold are set to a maximum value (255), and pixels below the threshold are set to zero.
- THRESH_BINARY_INV: Inverse binary thresholding. Pixels with values above the threshold are set to zero, and pixels below the threshold are set to a maximum value (255).
- THRESH_TRUNC: Truncated thresholding. Pixels with values above the threshold are set to the threshold value, and pixels below the threshold remain unchanged.
- THRESH_TOZERO: Thresholding to zero. Pixels with values above the threshold remain unchanged, and pixels below the threshold are set to zero.
- THRESH_TOZERO_INV: Inverse thresholding to zero. Pixels with values above the threshold are set to zero, and pixels below the threshold remain unchanged.
- THRESH_OTSU: Otsu's thresholding method. The threshold value is automatically determined using Otsu's algorithm, maximizing the separation between foreground and background pixels.
- THRESH_OTSU_INV: Inverse Otsu's thresholding method. Similar to THRESH_OTSU, but with inverted thresholding results.
- Threshold [Min, Max]: Adjust the minimum and maximum threshold values. The available range is 0 to 255. This property is visible when a thresholding type other than THRESH_OTSU or THRESH_OTSU_INV is selected.
- 1.Drag and drop the
Image Thresholdnode from the node library onto the canvas in AugeLab Studio. - 2.Connect the input image to the ImageAny input socket of the
Image Thresholdnode. - 3.Configure the threshold type and adjust the threshold values if needed.
- 4.Run the pipeline.
- 5.The
Image Thresholdnode will apply thresholding to the input image and provide the thresholded binary image at the ImageGray output socket. - 6.Retrieve the thresholded binary image from the output socket for further processing or visualization.
- The
Image Thresholdnode expects grayscale or single-channel input images. If the input image is in color, it will be converted to grayscale before thresholding. - The thresholding operation classifies pixels into two categories: foreground and background. Foreground pixels have values above the threshold, while background pixels have values below the threshold.
- The thresholded binary image produced by the
Image Thresholdnode has a pixel value of 255 for foreground pixels and 0 for background pixels. - The thresholding type determines the behavior of the thresholding operation. Each thresholding type has different characteristics in terms of separating foreground and background pixels.
- The Otsu's thresholding method automatically calculates the optimal threshold value based on the image histogram, maximizing the separation between foreground and background.
- By adjusting the threshold values, you can control the sensitivity of the thresholding operation and tailor it to your specific application.
That concludes the documentation for the
Image Threshold node in AugeLab Studio. This node allows you to apply thresholding to an input image, converting it into a binary image based on a specified threshold value.