Determining linear displacement in pixel units using linear patterns [video input]

I have a footage of a needle moving vertically, I would like to measure the vertical displacement of the needle in the video. I have first threshold the footage to isolate the features as shown in the image below.

Side-by-side comparison:

I just used simple binary threshold to get the features. as shown in code below

def detect_edges(frame):    # Convert the frame to grayscale    gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)    # Apply Gaussian blur to reduce noise    blurred = cv2.GaussianBlur(gray, (9, 9), 0)    # Apply thresholding    _, thresholded = cv2.threshold(blurred, 180, 255, cv2.THRESH_BINARY)    return thresholded

The pattern needs to be tracked between subsequent frames to get the linear displacement, I am thinking whether getting a mean of the intensity values in a vertical line on a small region in the frame would help to identify the presence of consecutive features. Then the pixel distance between features can be found as the features are such that Light regions are the feature while dark regions are spaces between them.

D-L-L-L-L-D-D-D.....D-L-L-L-L  ^                   ^

Is this a viable approach? And how could I approach finding displacement of the feature between consecutive frames using the intensity values.