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Algorithm for Sequence Image Automatic Mosaic Based on SIFT Feature

机译:基于SIFT特征的序列图像自动拼接算法

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Constraining by camerasȁ9; view-angles of the outdoor monitoring systems, the panoramic digital images fail to be obtained directly from photographing. A method is proposed on the basis of the scale invariance feature transform (i.e. SIFT) algorithm to stitch images captured by the turning video cameras together to form panoramic images. Based on the SIFT features and the retrofitted KD-Tree structure, the BBF searching strategy is employed to match feature points. Then in a post-processing pass, the Ransac algorithm is adopted to remove the mismatching feature points. Photos captured by a surveillance camera are taken as the input to test the proposed method. According to the test, the whole processing time of stitch is reduced while the fidelity of resulting stitched panoramic images is ensured.
机译:受相机约束ȁ9;从室外监控系统的视角来看,全景数字图像无法直接通过拍照获得。提出了一种基于尺度不变特征变换(SIFT)算法的方法,将转向摄像机捕获的图像拼接在一起,形成全景图像。基于SIFT特征和改进的KD-Tree结构,采用BBF搜索策略来匹配特征点。然后在后期处理过程中,采用Ransac算法去除不匹配的特征点。将监视摄像机捕获的照片作为输入来测试所提出的方法。根据测试,在确保得到的缝合全景图像保真度的同时,减少了缝合的整个处理时间。

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