Extact ROIs from linescan images using a Blob Analysis

  • The blob analysis operators determine the features of objects in binary images. Such features are the area, center of gravity, contour length and coordinates of the minimal paraxial rectangle which fits over the obejcts in the image. These coordinates are also called the bounding box. As you can see the operator will output features and not images. To exctract an ROI from the original image which fits exactly over the object the bounding box coordinates need to be used in a second step using operator ImageBufferMultiRoI.

    For area scan images and line scan images with dedicated image triggers this is easy to implement. However for linescan applications acquiring images of infinite height and arbitrary object posititions it is more difficult as the object could be at the cutting position between images.

    This example shows how to extract blob ROIs from the data of linescan cameras. To overcome the limitation explained above, we use two overlapping sliding windows as an input of the Blob_Anaylsis_2D operator.

    The example is available in two version. The simplified version does not care about dummy pixel caused by the parallelism granualrity and does not append meta information about the ROI size and sequence index. This is done in the advanced version. For a beginner, the simplified version is easier to understand before looking at the advanced version.

    The designs can fully be simulated with the attached image.