Step 1: Find Lanes

  1. The user draws a boundary that encloses all lanes on the image (even if some lanes will not be used for analysis). This is called the Region of Interest (ROI).

    Empiria Studio performs the rest of the lane finding and lane quantification process automatically.

    Empiria Studio boundary being drawn around lanes on a blot to start adaptive lane finding algorithm

  2. The ALF process begins by dividing the ROI into horizontal segments.

    Empiria Studio divides the image into segments for adaptive lane finding process

  3. Intensity of pixels in each horizontal segment is summed along the y-axis to find a segment intensity profile (SIP). The SIP is a cross-section of lane intensity along the x-axis for each of the horizontal segments.

    Segment intensity profile from the Empiria Studio adaptive lane finding process

  4. Intensity peaks within each SIP are analyzed to determine lane width, and lane widths are compared across SIPs to determine the left/right boundaries of the entire lane.

    Lanes found on a Western blot by the Empiria Studio adaptive lane finding algorithm

At the conclusion of this process, the lanes have been identified for further analysis, including background subtraction. The ALF process has identified the widths of the lanes, and the top/bottom of each lane corresponds to the ROI defined by the researcher.