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There are different methods to extract the length of vessels from a photo using Matlab, but a common approach could be:

1. Preprocessing: Enhance the image to improve the contrast and reduce noise. This can be done with filters, such as median or Gaussian, and with morphological operations, such as opening or closing.

2. Segmentation: Identify the vessels in the image by separating them from the background and other objects. This can be done with thresholding, region growing, or machine learning algorithms.

3. Skeletonization: Reduce the vessels to a thin line that represents their centerlines. This can be done with morphological thinning or distance transform algorithms.

4. Analysis: Measure the length of the vessels by computing the distance between their endpoints or by tracing along their centerlines. This can be done with graph theory algorithms, such as Dijkstra's shortest path or the A* search algorithm.

5. Postprocessing: Refine the results and visualize them if necessary. This can be done by filtering out false detections, merging broken segments, or displaying the length measurements on top of the original image.

Overall, the specific implementation of these steps depends on the characteristics of the image and the vessels being analyzed, and may require some tuning and experimentation.