To solve geometric distortion and misalignment generated in the traditional microscopic image stitching process and avoid low matching rate and high computational burden caused by rare features, a stitching algorithm based on the regional frog leaping search algorithm and image contour matching is proposed. First, the image contour curves of continuous acquisition and overlapping regions were extracted. Then, the clue-aware trajectory similarity or mean square error distance was introduced to calculate the similarity and discrete distance between image contour curves. Finally, the regional frog leaping algorithm was used in the decision domain, and by updating the tweet decibel and frog leaping strategy, optimal contour matching for the image was searched. Consequently, the images were stitched quickly and accurately. Experimental results verify that the proposed algorithm demonstrates high stitching precision and strong robustness. In addition, the simplified matching strategy reduces the amount of calculation and exhibits strong timeliness.