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This study proposes an improved feature-point matching and 3D registration method for augmented reality tourism applications. This method addresses issues such as poor alignment, low stability in complex environments, and low feature-matching accuracy. An improved feature point matching method for tourism images is introduced, which combines the Speeded Up Robust Features (SURF) algorithm with an enhanced Oriented FAST and Rotated BRIEF algorithm. In this method, feature points are initially detected using the SURF algorithm, and their orientation is determined via wavelet response analysis. The Lucas-Kanade optical flow method is employed for feature point tracking. The random sample consensus algorithm is then used to eliminate mistracked points. Furthermore, an augmented reality tourism 3D registration technique based on an improved homography matrix is proposed to overcome the limitations of traditional homography matrices, such as low matching accuracy and registration efficiency. The performance of the proposed method was analyzed through comparative experiments against the SIFT, SURF, and original ORB algorithms under various image transformations, including scale, blur, illumination, and rotation. The correct matching rate and matching time were used as evaluation metrics. Simulation tests were conducted for 3D registration using different 3D models. Registration accuracy and successful registration counts were evaluated under rotational changes. The outcomes indicated that the average correct matching rate of the proposed algorithm is increased by 44.08%, 36.51%, and 16.09% under scale variation than the scale invariant feature transformation algorithm, speeded up robust features algorithm, and unimproved algorithm, respectively. The correct matching rate under fuzzy transformation increased by 33.46%, 19.65%, and 9.35%, respectively. The average registration accuracy of the proposed 3D registration technique was 98.74% under rotational transformation. The outcomes reveal that the study's suggested approach can successfully improve the scene's virtual and real-world fusion effect and offers a fresh approach to the use of augmented reality technology in the travel industry.