The Automatic Image Anomaly Detection System (AIADS) algorithm takes a candidate image, and a historical set of images which intersect the candidate and precede it in time, and produces a heat map image of the same dimensions as the candidate, which marks anomalous regions as red and non-anomalous regions as blue or transparent. AIADS filters out normal changes (e.g. cars moving on a busy roadway, seasonal variations in vegetation, normal natural and man-made changes) and rapidly detects the most unusual changes so that further analysis can be conducted on only the most important changes.
Note: The following actions and parameters are needed such that the block works properly.
- Insert at least 5 input images
- Use the contains filter
- Using the DRA (Simularity) block in advance is not mandatory, but can improve results.
You can find more information on the provider website here.
[ "red", "green", "blue", "alpha" ]
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