What this tutorial covers
Import a test image and run an edge-detection workflow.
Before you start：You need access to the product and should ideally follow the tutorial using your own real parameters or data. The screenshots below were manually rematched to avoid the image/topic mismatches seen in the previous version.
Step-by-step workflow
1Open the module
Open Edge Detection under Image & Signal Algorithms. Confirm that the visible page really matches the tutorial topic before changing any settings.
2Configure the input
Prepare and check the input image, edge-detection method and any required thresholds.
3Run and watch the status
Choose the image, run edge detection and compare the input image with the detected output. Watch the visible status, plot or log area while the workflow is running.
4Inspect the result
Pay special attention to the detected-edge image and the processing settings used to obtain it.
5Verify and iterate
When noise is heavy, adjust thresholds or preprocessing first before comparing algorithms. Change one meaningful parameter and rerun so you can verify whether the output changes in the expected direction.
How to read the result
- The main output of this workflow is the detected-edge image and the processing settings used to obtain it.
- Read the result together with the exact inputs used for the run; a screenshot alone rarely tells the whole story.
- When noise is heavy, adjust thresholds or preprocessing first before comparing algorithms.
Troubleshooting & practical tips
- If nothing changes, first confirm that the correct module is open.
- If the output looks unrealistic, check units, field mapping and input scale first.
- For comparisons, change one key parameter at a time whenever possible.